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Revealing the genetic roots of obesity and type 2 diabetes Vliet-Ostaptchouk, Jana Vladimirovna van

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Download date: 01-10-2021 Chapter 2

Genetic variation in the hypothalamic pathways and its role on obesity, review

Jana V. van Vliet-Ostaptchouk, Marten H. Hofker, Yvonne T. van der Schouw, Cisca Wijmenga, N. Charlotte Onland-Moret

Obesity Reviews. 2009 Nov; 10(6):593-609 42 Chapter 2 Genetic variation in the hypothalamic pathways and its role on obesity consider multiple genes from the same physiological pathways, together with with together pathways, physiological same the factors. risk environmental from genes multiple should studies consider Such used. approaches analytical different and considered be should phenotypes obesity specific suggest obesity, we common of architecture genetic the of However, understanding our improve obesity. genes. To candidate many for to inconclusive still are findings predisposing in genes hypothalamic the for role important an support scans, association genome-wide in identified loci new,obesity the as common, well as studies, genetic and obesity. functional to from Together,data relation in genes candidate hypothalamic the on studies genetic review and regulation, weight body in animals. and humans in obesity for susceptibility the to contribute therefore may in role pathways theinhypothalamic ingenes the central disorder. variations the of a Genetic pathogenesis in system crucial a represent plays may circuits hypothalamus regulatory its weight, the body controlling As individual’s obese. the in becoming genes to of role predisposition significant the indicate studies adoption and twin multiple style, life (Western) modern to attributable mainly is epidemic this Although worldwide. dramatically increased has obesity of prevalence the decades recent Over Abstract We summarize current knowledge on the physiological role of the hypothalamus hypothalamus the of role physiological the on knowledge current summarize We currently more than 1 than more are currently there Organization Health World the to According 2). (1, worldwide dramatically Over the past two decades, the prevalence of overweight and obesity and overweight of prevalence the decades, two past the Over Introduction pathways regulating body weight in the etiology of obesity. We have chosen to focus focus to chosen have We obesity. of etiology the in weight body regulating pathways epidemic. obesity the to contribute may significantly variation genetic to due pathways regulatory its in efficiency altered 12). (11, weight body of regulation thus and balance energy affect part, in that, factors environmental and behavioral genetic, multiple between interplay of complex result a the likely most is epidemic for obesity predisposition current the the Altogether, in 12). (11, obesity variation explain may susceptibility genetic in have differences studies family and adoption- twin-, indicated a of Many contribution significant genetic factors Therefore, obesity pathogenesis. to overfeeding. to due weight body increased for predisposition the in variability individual wide a is there development, disease for required is balance energy of disruption chronic a Although intricate. more (10). humans in obesity of forms monogenic severe cause to known are pathways regulatory these in genes of functioning normal the disrupting mutations single Indeed, weight. body of deregulation a to lead can system this in defects any but (8), people most in time the of most in stable remarkably remains changes weight body result, a induce As metabolism. and to behavior transmitted and interpreted received, are from systems signals multiple peripheral which in process physiological complex this in role key a plays hypothalamus The 9). (8, body the in metabolism energy of homeostasis the regulates body fat (1). Both food intake are by controlled the and expenditure energy brain, which as calories excess of to storage leading expenditure, energy and calories) consumed (or (1). century this of problems health public major the of one declared been has it 7), (6, diabetes 2 type and hypertension disease, cardiovascular including diseases, chronic for various risk a higher with associated strongly is obesity Since 3-5). (1, decreased has activity physical time, same the at while, sugars and fats in high foods of consumption greater to shifted have habits eating – style life our in changes to attributable mainly of which at least 300 million are clinically obese (BMI ≥30 kg/m ≥30 (BMI obese clinically are million 300 least at which of Here we examine the impact of genetic variation in the hypothalamic signaling signaling hypothalamic the in variation genetic of impact the examine we Here link the in represents ofcrucial the bodyregulation the Since weight, hypothalamus is obesity common of nature the obesity, of forms monogenic rare the to Contrary intake food between imbalance long-lasting a from result obesity and Overweight

billion overweight adults (body mass index (BMI) ≥25 kg/m ≥25 (BMI) index mass (body adults overweight billion 2 ) (1). This epidemic is is epidemic This (1). )

has increased increased has 2 ), ), 43 Chapter 2 Genetic variation in the hypothalamic pathways and its role on obesity 44 Chapter 2 Genetic variation in the hypothalamic pathways and its role on obesity addition, the the availability addition, In (14-16). weight body heavier or intake food increased with associated are leptin the signaling or via insulin either way in defects similar hypothalamic a that known in is It acts (15). pathways Insulin same receptors. leptin the via pathways hypothalamus appetite-stimulating the activates in which falls, leptin of level the restricted, is food when contrast, In feeding. inhibits plasma in concentration high to its and fat, proportional body levels at circulates Leptin (14). insulin pancreatic and adipocytes, by body from information stores energy to the hormones brain and are via circulating mediated feedback provide signals and Adiposity hungry (13). when appetite stomach the stimulates by secreted is ghrelin over-consumption. peptides, prevent these hence, to contrast and, In feeling satiety the mediating by via intake the from cholecysto signals releases gut satiety the food intake to of response In signals. related integration nutrient and the adiposity (GI), tract involves gastrointestinal balance energy of Control periphery the from signals Input rate. metabolic the and feeling) satiety or food for searching (e.g. behavior adjusting by these to responds it and system peripheral the from signals receiving constantly is hypothalamus the process this During metabolism. and feeding have the studies keyAnimal demonstrated role in of of the regulation the hypothalamus balance energy regulating in hypothalamus the of role The diseases. complex and variants genetic between on relationship the studies genetic in considered analyze to strategies and statistical be phenotype obesity the of definition as obesity, such should that issues important will several We genes. discuss these on performed studies association genetic the review then and weight, body regulating in receptors and peptides the of role the explore will we First homeostasis. energy monitoring in involved (2) hormones peripheral and the for receptors the intake, food regulating in involved network signaling hypothalamic the from neuropeptides major the (1) pathways: these in players key the encoding genes the on mechanisms described in different hypothalamic regions (17). regions hypothalamic different in described mechanisms

of blood glucose or fatty acids is monitored via specific sensing sensing specific via monitored is acids fatty or glucose blood of kinin (CCK) and peptide YY (PYY) that inhibit food food inhibit that (PYY) YY peptide and (CCK) ­kinin – leptin, produced produced leptin, of obesity on a high-fat a on obesity of development the accelerates it LHA to the in while weight, body in gain regions and hyperphagia brain different in induces PVN the in disruption its e.g. signaling syndrome, obesity the of characteristics different melanocortin of contribution rodents the in studies indicate Functional rate. metabolic increasing on and intake being effect food major decreasing its with balance, energy the controlling in important Especially is (LHA). MC4R hypothalamus lateral expressing the and neurons (PVN) nucleus paraventricular “second-order” the as to sent are such hypothalamus, the of parts other to and MC4R and MC3R neurons receptors melanocortin ARC the from Signals nucleus arcuate the of signaling Downstream intake. food of reduction to leading cells, POMC/CART by mediated pathway anorexigenic the switch and neurons NPY/AGRP of via system. CCK,transmitted PYY, These signals the andsuppress leptinactivation insulin peripheral the from signals input for receptors many express neurons ARC of sets Both (19). (GABA) acid gamma-aminobutyric by mediated cells POMC/CART of on activity effect the inhibitory an have neurons NPY/AGPR The (18). balance energy positive conditions of under stimulated are and (CART), transcript amphetamine-regulated and cocaine- and (α-MSH), hormone stimulating alpha-melanocyte secreted the via intake neuronsact via pro-opiomelano appetite-suppressing Other (17). hunger increased and loss is weight of conditions in activity observed neuronal their as intake food of drivers The are (AGRP), protein (18). agouti-related neurons “first-order” are periphery, orexigenic the from signals multiple sensing hypothalamus, the of (ARC) nucleus arcuate the in populations neuronal different Two hypothalamus the in signals peripheral of integration The circuit regulates satiety (18). (18). satiety regulates circuit regions in located different hypothalamic are which receptors, (5-HT) nutritional 5-hydroxytryptamine to and (23), response signaling in MC4R intake via status food is decreases which and nucleus (BDNF), VMN factor the in neurotrophic secreted brain-derived the (21); under behavior fasting of food-seeking stimulates conditions and (22) LHA in widely expressed is orexin, which are regulation appetite in players important been Among have 21). 18, circuits (17, in these reviewed intake; food regulating in involved are pathways thalamic In addition, many other peripheral hormones and neuropeptides from the hypo/ the from neuropeptides and hormones peripheral other many addition, In or appetite-stimulating neurons, producing the neuropeptide Y (NPY) and (NPY) Y neuropeptide the producing neurons, appetite-stimulating or

diet (20). (20). diet and through which s which and through cortin (POMC), that ­cortin (POMC), suppress food erotonin from the reward erotonin (see anorexigenic Figure 1 Figure ) or or

45 Chapter 2 Genetic variation in the hypothalamic pathways and its role on obesity 46 Chapter 2 Genetic variation in the hypothalamic pathways and its role on obesity Sero St tonin omach PVN New obesity gene GNPD PTER, TMEM18 Ghr NEGR1, NPC The h AR FT ? elin A2, HTR2A C SCG3 O Ghsr ?? ? ypothalamu ? KC TUB ? TD15, Npy2 BDNF 1 FT NMU , AGRP s MTMR9 O NP r ?? s ? GI tr Y LepR act MTMR9 Glucos Mc3r Lipids InsR in F ? SCG3 ood take ?? GAD2 Npy5 e in F Npy1 ood take r FT ?? r O MCH Mc4r TUB ?? MTMR9 in GABA F expenditur take ood ?? Mc2r Adipose Mc1r ssue Energy LHA Or MCHR2 CCK PY exin Npy1 Y e r αMSH POMC BDNF InsR CART LepR MCHR2 PCSK1

?? TUB ?? LepR FT InsR ?? Mc3r SCG3 Insuli Lep O ?? Pancreas SH2B1 VMN n ?? n hypothalamus; UBL5, ubiquitin-like 5. ubiquitin-like UBL5, hypothalamus; the of nucleus ventromedial VMN, homolog; tubby transmembrane TUB, III, TMEM18, secretogranin SCG3, 18; homolog; protein SH2-B SH2B1, YY; peptide PYY, hypothalamus; the of nucleus paraventricular PVN, gene; phosphotriesterase-related POMC, PTER, Y5; receptor Y proopiomelanocortin; Y1 neuropeptide neuropeptide NPY5R, Y2; NPY1R, receptor Y Y; neuropeptide neuropeptide NPY2R, NPY, receptor; C1; type neuromedin disease, NMU, niemann-Pick B; NPC1, neuromedin U; NMB, 1; regulator growth neuronal NEGR1, hormone; 9; protein melanocortin-4 related MC4R, myotubularin receptor; receptor;MTMR9, melanocortin-3 MC3R, receptor; receptor; melanocortin-2 melanocortin-1 MC2R, MC1R, receptor; hormone melanin-concentrating MCHR2, area; hypothalamic lateral LHA, receptor; leptin LEPR, receptor; insulin INSR, 15; containing domain receptor; tetramerisation channel KCTD15, receptor; secretagogue potassium (serotonin) 5-hydroxytryptamine HTR2A, hormone growth GHSR, tract; gastrointestinal glutamate GI, GAD2, 2; acid; decarboxylase gamma-aminobutyric GABA, obesity-associated; and mass fat FTO, cholecystokinin; CCK, transcript; cocaine-amphetamine-regulated CART, factor; neurotrophic Abbreviations: red). in (highlighted unknown still is pathways regulating weight body the in role their however obesity, with associated be to reported are hypothalamus the from genes New balance. energy providing expenditure energy and intake food in changes to transformed and transmitted are signals multiple These serotonin). via (e.g. behavior feeding reward-inducing modulate that signals receives hypothalamus the addition, In status. energy by regulated neuropeptides expressing (VMN), nucleus ventromedial the or intake are located; food reducing neurons where (PVN), nucleus paraventricular the gain; weight promoting and intake food stimulate that neurons containing and center” “hunger a be to known (LHA), area assuch the areas, lateral hypothalamic on project to differentsignals hypothalamic effect.Both opposite the have neurons POMC/CART whereas intake, food promotes neurons NPY/AGRP of activation The cells. of groups POMC/CART-producing NPY/AGRP- and contain which nuclei, or (+) stimulate (–) ofinhibit the areproduction peptides by received that inthereceptors hormonal thevarious ARC bottom) the at (shown nutrients circulating and diet to related Signals behavior. eating and homeostasis 1: Figure The interactions between the neuropeptides in the hypothalamus regulate energy energy regulate hypothalamus the in neuropeptides the between interactions The AGRP, agouti-related protein; ARC, arcuate nucleus; BDNF, brain-derived brain-derived BDNF, nucleus; arcuate ARC, protein; agouti-related AGRP,

α-MSH, alpha-melanocyte stimulating stimulating alpha-melanocyte α-MSH, 47 Chapter 2 Genetic variation in the hypothalamic pathways and its role on obesity 48 Chapter 2 Genetic variation in the hypothalamic pathways and its role on obesity that variants in the following genes are associated with the risk of obesity: obesity: of risk the with 26), associated (25, are genes following the in variants showing that published, been have genes 21 these of 11 on studies Since new 2005 (24). November update HOGM last the in phenotypes obesity-related with associated be to reported genes 21 including interscience.wiley.com/journal/122440250/suppinfo), pathways have ( examined been hypothalamic the from obesity for genes candidate 27 of total a 2009, January 1 of As obesity common for studies association gene Candidate selected. were 2009 January and 2005 November between published publications 107 review the For in (specified phenotypes, neuropeptides hypothalamic the for obesity names gene individual different and studies, genetic for keywords of combination a using our combined search PubMed a and performed We update. HOGM that from (24), information the with results 2005 in comprehensive project HOGM last the the by out after carried review published literature studies association genetic explored only all evaluated extensively of obesity. to has relevant genetics areas the in Weresearch the therefore results published project (HOGM) Map Gene Obesity Human the 1996, Since pathogenesis. obesity the to pathways regulatory hypothalamic the in variants genetic of contribution the examine to review literature large-scale a performed We pathways hypothalamic the in genes in studies Association obesity. to thus, and, weight body of deregulation a to lead system this in defects anyand balance energy role in regulating pathways play a crucial hypothalamic the that (10)). and O’Rahilly Farooqi by paper the see review comprehensive a (for obesity severe extremely obesity), of form monogenic common most (the including genes, in functioning normal the disrupting mutations single example, For balance. energy regulating in pathways hypothalamic of nature fundamental the has phenotypes provided novel into insights the of pathogenesis and obesity highlighted human extreme of study However, the a population. obese only the of percentage represent small very mutation gene single a by caused obesity severe with patients The genes hypothalamic the in mutations to due obesity Severe

In summary, studies in animals and severely obese patients have demonstrated demonstrated have patients obese severely and animals in studies summary, In BDNF BDNF (26-29), (26-29), GAD2 GAD2 (30), (30), Supplementary Table 1 Supplementary HTR2A (31, 32), 32), (31, POMC, POMC, LEPR LEPR , available online: http://www3. , online: available (33-41), (33-41), or leptin receptor, lead to lead receptor, leptin or MC4R MC4R (42-53), (42-53), Figure 2 Figure MC4R MC4R AGRP AGRP NPY NPY ). ). MeSH terms: “Hypothalamus” MeSH terms: "Overweight" MeSH terms: "Polymorphism", "Polymorphism, Single Nucleode" Text Word: hypothalamus, neuropepde Text Word: overweight, obesity, body weight, Genes included in the search: AGRP, BDNF, BRS3, CART, CCKAR, CCKBR, CRH, CRH1, weight, body mass index, BMI, body fat mass, fat, Text Word: gene, genec, variaon, CRH2, FTO, GABRA6, GABRG3, GAD2, GAL, GALR, GCGR, GHR, GHRH, GHSR, GRIN1, body fat, abdominal fat, fat-free mass, skinfold, polymorphism, variant, SNP, associaon HCRT, HTR1B, HTR2A, HTR2C, INSR, LEPR, MCHR1, MCHR2, MC3R, MC4R, MC5R, NMB, waist, waist circumference, hip, hip circumference, NPY, NPY1R, NPY2R, NPY5R, NTSR1, POMC, TUB, UBL5 waist-hip rao

2,167,630 205,053 906,521 arcles arcles arcles

Combining the searches 1 AND 2 AND 3, limited to human studies and publicaon Combining the searches 1 AND 2 AND 3, limited to human studies, published during the last date a er 1 Nov 2005 (up to then all publicaons in the field of obesity genecs were year (Jan 2008 - Jan 2009) incorporated in the last (12th) update of the human obesity gene map (HOGM)): ONLY the publicaons indexed for MEDLINE were included This search idenfied all relevant publicaons that were not indexed in PubMed

576 474 arcles arcles

– Included studies reporng genec associaons with obesity or obesity-related phenotypes

– Excluded studies reporng genec associaons with monogenic forms of obesity; with the effects of medicine on body weight gain; with weight loss; with birth weight, with eang disorders only, related to mutaon screening without a follow-up populaon-based study

106 arcles were selected a er reading the abstract Figure 2: Criteria and strategy used in the PubMed search for relevant publications. A PubMed search was performed using a combination of keywords for genetic studies, different obesity phenotypes, and individual gene names for the hypothalamic neuropeptides. In order to identify the names of the genes coding these proteins, we used the Entrez Gene database at the National Center for Biotechnology Information (NCBI) (http://www.ncbi.nlm.nih.gov/sites/entrez). Multiple gene names were found for several proteins, for which we then selected the human gene names using the HuGE Navigator database (http://www.hugenavigator.net/HuGENavigator/startPagePedia.do), and the HOGM database (http://obesitygene.pbrc.edu/). Altogether, 40 gene names were included in the search based on their function, including two newly identified candidate genes for obesity, FTO and TUB. Since the last update of HOGM (in November 2005), 576 studies were retrieved in PubMed using the keywords combination. Since only the articles that were indexed for MEDLINE were found in that search, we also screened relevant publications by checking all the studies published during the last year that were not yet indexed. After carefully reading the abstracts, 106 publications were selected for further reviewing, these were published between November 2005 and 1 January 2009, plus one just published genome-wide association on early onset and morbid obesity (135). 49 Chapter 2 Genetic variation in the hypothalamic pathways and its role on obesity 50 Chapter 2 Genetic variation in the hypothalamic pathways and its role on obesity associations between genetic markers in markers genetic between the associations reproduce to unable were studies other afew studies, positive these to addition (54-56), (41, 66-68), (41, 109) investigated in candidate gene association studies: studies: association gene candidate in investigated (24) update HOGM last for reported also were findings Negative phenotypes. related reviewed, we consider ( five we consider reviewed, ( map gene obesity human the from and literature reviewed the from association the for evidence the all summarized have we obesity, to the in genome-wide association studies (GWAS) finding for the the for finding original (GWAS) the studies replicating association studies genome-wide were papers) (36 one-third review, this for selected that provided support for of role the the protective support that provided MCHR2 for published been have studies replication No 115). (114, fat central percentage and the of findings original of effect the supported studies independent Two (117-121). for obesity models mice in studied previously were and hypothalamus the of areas different (116). pathway melanocortin the from protein neuropeptides PC1 the of processing of the in involved activity enzymatic reduced the to leads which change, amino N221D SNP nonsynonymous associated The (112). ancestry European individuals of 13,659 of total a in investigated was obesity, monogenic cause to known from the hypothalamic pathways to be of particular interest. The role of of The role interest. particular of to be pathways hypothalamic the from gene candidate Next, susceptibility. obesity in GHSR of further role the of requires investigation results the in consistency of lack This (109). cohort population UK a from children and adults 6600 than more of study another in found was BMI or weight common between relationship no (106-108), association positive a reported populations Chinese and Finnish in studies size sample moderate two and countries, European Western 10 from individuals 3600 than more comprising was obesity investigatedin four recentWhile studies. study,one large, population-based in variants the between association The association. original the confirmed After the last HOGM update, six new genes from the hypothalamic pathways were were pathways hypothalamic the from genes new six update, HOGM last the After To prioritize the importance of the 27 candidate genes regarding their contribution contribution their regarding genes 27candidate the of Toimportance the prioritize Several meta-analyses were published between November 2005 and August 2008 2008 August and 2005 November between published were meta-analyses Several Other new candidate genes – – genes candidate new Other , MCHR2 , MC4R and and NPY2R TUB TUB MC3R MC3R gene against human obesity at a population level (43, 122). 122). (43, level population a at obesity human against gene NMU (110), (110), on BMI (113) and also reported the association with waist circumference circumference waist with association the reported also and (113) BMI on (57-60), (57-60), yet, hence their role in obesity genetics remains to be clarified. clarified. be to remains genetics obesity in role their hence yet, (49), NMU . MC4R MC4R POMC POMC (111), (111), FTO, HTR2C, LEPR, MC4R, PCSK1 MC4R, LEPR, FTO, HTR2C, (51, 69-71), (51, (61, 62), and and 62), (61, PCSK1 MCHR2, NMU, MCHR2, (112) and (112) AGRP AGRP NPY NPY UBL5 UBL5 (57, 72), (57, (54), and TUB TUB V103I 6) ( (63) FTO FTO al 1) Table BDNF BDNF TUB

(113-115). Of the 107 papers papers 107 the Of (113-115). and the and and (52, 66, 74-105) 66, (52, Suppl FTO ) of the 32 genes examined examined genes 32 ) the of – are highly expressed in in expressed highly are – GHSR GHSR (26), . Based on the literature literature the on Based . NPY2R NPY2R gene and the majority majority the and gene BDNF, LEPR, NPY LEPR, BDNF,

al 1 Table GAD2 GAD2 I251L variation and body body and variation rs6232 (73) with obesity- with (73) polymorphisms polymorphisms FTO ). However, in in However, ). (64, 65), (64, , encodes for encodes

GHSR GHSR and and GHSR GHSR PCSK1 in the the in MC4R LEPR LEPR (106- and and , account are needed to clarify the genetic contribution to the pathogenesis of obesity. of pathogenesis the to contribution genetic the clarify to needed are account into phenotypes obesity takespecific that populations large in studies replication Thus, studies. later by confirmed always not were associations the because or lack information of of because either open, remain genes 22 other the for conclusions The cohorts. family-based and case-control independent eight from study large-scale a in reported (125). performed study to isofjudge the necessary thequality association information genetic (123). variant causal another with variant genetic examined the of due be correlation can the in differences phenomena, to flip-flop or populations, different in disease the with allele structure same the for (LD) ofassociation directions opposite Indeed, (65). region genomic this disequilibrium within linkage in differences interpopulation or (64) samples association in the variant Finally, functional the disease. of to contribution their supporting 10 in studies, replicated more and positively was respectively, phenotypes, obesity different and gain and gene- candidate For studies. multiple association in genome-wide established strongly been has genetics obesity in positive replication published recently (24, 30). Several explanations for this for explanations Several the 30). and (24, finding recently published original the replication positive to compared with 65) (243A→G) (64, direction rs2236418 opposite of the in association obesity the reported studies two latter, the For in compelling variation that no evidence is there literature, reviewed the from example, For of obesity. studies common genetic in problem major a remains associations of the that reproducibility of showed lack clearly studies gene candidate on literature selected the Exploring studies association between Inconsistency ( the of equilibrium Hardy-Weinberg orcall the rate,control for genotyping studied, homogeneity population ethnical publications, the of one-third almost in that, observed also we studies, selected the reviewing While (124). studies replication the of power of lack the (5) or rate, error I type the of control inadequate the (4) studies, in analyzed phenotypes obesity different the (3) populations, between structure LD underlying the (1) non-replication be: for could reasons potential while findings, false-positive imply necessarily atrs f interacting background, of genetic in patterns differences as such suggested, were direction association of HWE In summary, inconsistency between candidate gene association studies does not not does studies association gene candidate between inconsistency summary, In ) were not mentioned by the researchers. This straightforward but important important but straightforward This researchers. the by mentioned not were )

ethnicity ascertainment criteria leading to population stratification, (2) stratification, population to leading criteria ascertainment ethnicity

niomna epsrs ciia faue bten h two the between features clinical exposures, environmental GHSR PCSK1, (as discussed above) and and above) discussed (as an attractive positional and functional gene, was gene, functional and positional attractive an HTR2C HTR2C and LEPR, the association with weight weight with association the GAD2 GAD2 contribute to obesity. obesity. to contribute

reversal reversal

51 Chapter 2 Genetic variation in the hypothalamic pathways and its role on obesity 52 Chapter 2 Genetic variation in the hypothalamic pathways and its role on obesity

Table 1: Evidence of association between genes from the hypothalamic pathways and obesity-related phenotypes based on genetic association studies. Gene Candidate gene studies Associated obesity Additional information** Ranking (positive/ negative results) phenotype FTO 36 / 4 OO, CO, BC MC4R 23 / 3 OO, CO, BC Monogenic obesity in humans, animal model BDNF 5 /2 OO Animal model SH2B1 1 OO, CO, BC Animal model GNPAD2 OO, BC A candidate gene from the identified locus Promising genes with a strong evidence KCTD15 OO A candidate gene from the identified locus for their contribution to common obesity, NEGR1 OO reported in genome-wide association studies NPC1 OO Identified in GWAS for early onset/ morbid obesity, animal model TMEM18 OO PTER / C10ORF97 OO Candidate genes from the identified locus from GWAS for early onset/ morbid obesity LEPR 24 / 5 OO, CO, BC Monogenic obesity in humans, animal model Promising genes for common obesity, HTR2C 10 OO Association with antipsychotic medication- showing replications in ten and more induced weight gain, animal model candidate gene studies NPY2R 7 / 2 OO, CO GAD2 7 OO AGRP 6 / 1 OO, BC Animal model Promising genes for common obesity NPY 5 / 2 OO, CO Animal model POMC 4 OO Monogenic obesity in humans, animal model PCSK1 1 OO Monogenic obesity in humans, animal model Gene Candidate gene studies Associated obesity Additional information** Ranking (positive/ negative results) phenotype HTR2A 4 OO, CO GHSR 4 / 1 OO, CO Animal model Promising genes for common obesity, TUB 3 OO, CO, BC Animal model however additional studies are required to CART 2 OO, CO Animal model clarify the role in the obesity pathogenesis MC3R 2 / 1 OO, BC Animal model UBL5 2 CO, BC CCKAR 1 BC Animal model CRHR1 1 OO Animal model for CRHR2 GCGR 1 CO, BC Animal model HTR1B 1 OO INSR 1 OO Not enough information, replication studies MCHR2 1 OO are required to clarify the role in the obesity MC5R 1 OO, BC pathogenesis MTMR9 1 OO NMB 1 OO, CO, BC NMU 1 OO, CO Animal model NPY5R 1 OO Animal model SCG3 1 OO MCHR1 0 no effect No effect on obesity-related phenotypes was NPY1R 0 no effect Animal model reported yet SCG5 0 no effect * Genetic association studies published up to January 2009 (all relevant studies published until October 2005 were reviewed based on the last update of the Human Obesity Gene Map project (24)).** The information on animal models of obesity and severe forms of obesity is based on the last update of the Human Obesity Gene Map project and the review by Farooqi and O’Rahilly (10, 24). Abbreviations: OO overall obesity, CO central obesity, BC body composition. 53 Chapter 2 Genetic variation in the hypothalamic pathways and its role on obesity 54 Chapter 2 Genetic variation in the hypothalamic pathways and its role on obesity mechanisms underlying the observed associations. observed the underlying mechanisms physiological the understand to needed haplotype be will a analyses within functional variants Additional cluster. causal of presence the (2) and susceptibility, disease differences in protein structural than rather products the protein reflect regulating SNPs of intronic importance these that (1) suggesting regions noncoding in located are variants variants identified common the of majority the new Furthermore, obesity. complex in role a play on that evidence reliable a provide that to indicate required results is These size BMI. sample large adult in variation the of proportion small a explains only effect combined their and allele, per BMI of units 0.33 to 0.06 from ranging large-scale. in effect modest replication very a has variants associated further the of Each >59,000). (n with studies follow-up individuals, 32,000 over of studies GWA 15 136-140). 134, (133, hypothalamus in the expressed are highly However, genes novel are these unknown. all transport (135), whereas the functions of of functions the whereas (135), transport are known to be involved in neural development (133, 134), 134), (133, development neural in involved be to known are from animal models studies (24). The functions of the other nine genes are not yet yet not are genes nine clear: other the of functions The (24). studies models animal from 60,000 SNPs identified identified SNPs 60,000 than more with populations Japanese in conducted GWAS small-scale two addition, In http://www3.interscience.wiley.com/journal/122440250/suppinfo). online: available – obesity morbid and early-onset for – TMEM18 hypothalamus SH2B1, the NEGR1, MC4R, in KCTD15, role a play may that genes near or in energy regulating metabolism. in in involved those over involved balance the genes in for role particularly key (and a brain suggesting the again in hypothalamus), expressed highly are that genes associated of highlight majority loci the Notably, (127-134). populations Caucasian in gene-discovery out carried powerful, a the representing – in (126), studies GWA were identified obesity To for common loci new approach. several date, variants – genetic project common HapMap of catalogue International comprehensive a with technology genotyping in advances latest the combine (GWAS) studies association Genome-wide obesity common for studies association Genome-wide The role of the the of role The 137). (136, findings these confirm to needed are studies independent from replications Some of these novel obesity genes were identified through a meta-analysis of meta-analysis a through identified were genes obesity novel these of Some So far, published large-scale GWAS have reported eight loci for common obesity obesity common for loci eight reported have GWAS large-scale published far, So FTO was to shown by be and (138), fastingfeeding regulated BDNF, MC4R BDNF, MTMR9 and and and and SH2B1 SCG3 NPC1 genes in obesity pathogenesis is well known known well is pathogenesis obesity in genes (127, 128, 130, 133-135), and two new loci loci new two and 133-135), 130, 128, (127, GNPDA2 as obesity susceptibility genes, although although genes, susceptibility obesity as and and PTER , , KCTD15, MTMR9, PTER MTMR9, KCTD15, (135) ( (135) Supplementary NPC1 BDNF, FTO, GNPDA2, GNPDA2, FTO, BDNF, NEGR1 is involved in lipid lipid in involved is and and and TMEM18

Table 1 Table SCG3 SCG3 , error rate automatically leads to reduced power. Thus, GWAS are often underpowered underpowered often are GWAS power. Thus, reduced to leads automatically rate error 1 type the of correction This studied. are phenotype the analysis with associated be statistical to considered the in correction multiple-test for threshold strict a markers pass only that and GWAS in genotyped are SNPs of thousands of hundreds Secondly, (146). identification their for power statistical sufficient provide to required therefore are studies large-scale and lower), or 1.2-1.3 probably are ratios odds estimated (the havewill a only to moderateeffect obesity contributing variants that common expected is it First, GWAS. in associated be to found not were phenotypes obesity-related with (43). disorder the against protective maybe variants obesity, gain-of-function to severe lead mutations function loss-of whereas trait: metabolic a on effect” “balanced a have and between monogenic and complex forms of the disease. Rare variants in in variants Rare disease. the of forms complex and monogenic between overlap possible of evidence provides This obesity. severe for cause frequent most the MC4R positive with a reported association studies gene candidate the all not although 145), 42-48, (26-29, and So far,GWAS So studies candidate and studies association genome-wide between Consistency genetic the to variation rare obesity. and of structure common of more contribution provide relative will the into sequencing insight deep and studies association large-scale in variants, number copy and deletions insertions, as such the variants, structural and rare of Therefore, inclusion (144). individuals lean with compared individuals obese among SNPs nonsynonymous rare, of excess an revealed date, to study large-scale only the mass, body human of extremes the with associated variants genetic for search extensive An diseases. common to susceptibility in variants rare of importance the highlight (143) drift) genetic and mutations random to due gain fat to a predisposing to genes in led change predation of absence the (e.g. hypothesis Release” “Predation the or (142), selection purifying weak underwent that SNPs deleterious slightly on hypotheses the contrast, In (141). ≥5% frequency allele minor with SNPs target thus, and, hypothesis variant” common disease, “common the on based is which data, HapMap on based are platforms genotyping GWA current-generation that remember to important also is It Several factors may explain why genes consistently reported to be associated associated be to reported consistently genes why explain may factors Several I251L) SH2B1 SH2B1 also contribute to the risk for common obesity. Coding mutations in this gene are gene in this mutations obesity. for Coding to risk common the contribute also are also shown to be protective for obesity (43, 122) suggesting the genes genes the suggesting 122) (43, obesity for protective be to shown also are with obesity that were previously examined in candidate gene studies studies gene candidate in examined previously were that obesity with

have BDNF

confirmed the association of the hypothalamic genes hypothalamic the of association the confirmed or or MC4R . Another interesting observation is that SNPs near near SNPs that is observation interesting Another . MC4R BDNF, MC4R ( V103I 55 Chapter 2 Genetic variation in the hypothalamic pathways and its role on obesity 56 Chapter 2 Genetic variation in the hypothalamic pathways and its role on obesity the definition of the obesity phenotype and methodological issues. methodological and phenotype obesity the of definition the bias. publication and recognized: not effects, often are which problems small important other two still are However, detect there to power of lack control, error 1 type of lack heterogeneity, study stratification, population by explained be can inconsistency such earlier, discussed as And, obesity. common to related in studies problem association genetic major the remains non-replication literature, reviewed the in saw we As obesity on studies association genetic in Pitfalls (152). studies replication of publication and conduct design, the for practices best of of criteria list a proposed publishing, scientific and genetics epidemiology, medicine, clinical biostatistics, including disciplines, diverse from experts of group a studies, association genetic in inconsistency to design leading factors these all 146). avoid help (141, To study limitations such to due excluded be cannot a GWAS in findings false-negative the that have necessarily mind in not tokeep important is it do Thus, population. another in population association or effect one same in disease a with associated that variants indicating 149-151), (132, populations Oceanic or Indians Asian Han, Chinese as between association the instance, GWAS. For and gene- candidate between inconsistency the to apply also (146-148), stratification population undetected and studied, populations in controls, and cases of ascertainment in allele, risk the of frequency the in differences results false-negative as (such studies gene to candidate between inconsistency of lead causes all Finally, 147). (146, could platforms genotyping the in variant associated genome human disease- true, the the for coverage good of absence in thus and ~80%) is coverage variations (estimated common the all capture not do chips SNP density Thirdly, high- even studies. gene by candidate found genes the of several confirm might and variants detect to power the increase will meta-analyzed which are GWAS in large several Collaborations GWAS. diabetes 2 type many the by associated significantly be to found not was but studies, gene candidate from disease to the with known associated also be was that diabetes 2 type of development the in role well-established is this of example good A might disease. they the but with GWAS associated in be up well picked not are risk the alter that sizes effect small with genes candidate several that means This (146). size effect small with genes detect to FTO and obesity has never been found in non-Caucasian populations, such such populations, non-Caucasian in found been never has obesity and PPARG , a gene with a with gene a , has also been shown that relative fatness in adults in fatness relative that shown been also has It (154). distribution fat of pattern the delineate it does nor overweight individuals), between muscular and possible is misclassification a differentiate (e.g. not tissue fat does and it lean levels, between distribution fat or fat body incorporate directly not does BMI since However, obesity. of a severity the and diagnosing measure, for to criterion easy well-defined calculate, to simple is their BMI of tool, square clinical a the As by 153). (1, divided height weight body individual’s the is BMI (1). respectively f vregt n oeiy s bd ms idx BI ≥5 kg/m ≥25 (BMI) index mass body a is obesity and overweight of definition common most the guidelines, Organization Health World the to According definition Phenotype way, even when BMI remains constant (i.e. there is a greater a is there (i.e. constant remains BMI when even way, than phenotypes to be taken into account in genetic studies on obesity (159). (159). obesity on studies genetic in account into taken be to phenotypes obesity of the specific the importance et highlighted al. Hasselbalch for trait (159). each specific be may contribution genetic that indicating obesity, of between measurements different correlations genetic high are there that later shown was it Moreover, BMI. for loci positive strongly any find to failed researchers families but individuals, 10,000 31,000 over and than more from data encompassing studies, linkage 37 from results the combined analysis This (158). obesity and BMI in studies linkage genome-wide of marker, best meta-analysis recent a the in suggested reasons was be the explanation same of The not one replication. of be lack for might could BMI BMI their on As based obesity. subjects obese of of misclassification marker a as BMI and genes studies. large-scale for unsuitable therefore and time-consuming and and expensive are methods (11) these but mass (157), imaging) ultrasonography and resonance fat (magnetic MRI central tomography), (computed quantifying CT are for fat visceral methods accurate More quantify to fat. thickness skinfold subcutaneous and obesity, abdominal measure to used ratio to-hip (156). smoking or stress patterns, dietary activity, physical as such factors, multiple of combinations different may havetwo theindividuals sameor weight phenotypes: BMI through obesity defining correctly of problems the to strongly contribute factors environmental defined poorly or unmeasured addition, In phenotype. obesity for marker best the be not might only, obesity overall measures which BMI, Thus fat body (155). percentage and BMI between Many of the association studies presented here investigate the relation between between relation the investigate here presented studies association the of Many waist- and circumference waist are parameters obesity-related common Other

in women) and that there are national- are there that and women) in

or ethnic differences in the relationship relationship the in differences ethnic or

increases with age in a sex-specific sex-specific a in age with increases

relative increase in men men in increase relative 2 n ≥0 kg/m ≥30 and 2 , 57 Chapter 2 Genetic variation in the hypothalamic pathways and its role on obesity 58 Chapter 2 Genetic variation in the hypothalamic pathways and its role on obesity (wais with specific obesity phenotypes ( phenotypes obesity specific with gene each of associations the explored we obesity, of measures different to contribute fat, total fat mass, body fat. body mass, fat total fat, total abdominal abdominal, diameter, subcutaneous abdominal sagittal mass, lean percentage, bodyfat mass, free fat asmass, fat such measurements –different by phenotypes composition ratio;body and – waist-hip by waist and hip circumferences phenotypes obesity central weight; body and BMI by indicated are phenotypes obesity general) (or Overall phenotypes. related 3: Figure on life style and dietary patterns for different ethnic groups in different subpopulations. indifferent groups ethnic different for patterns dietary on and life style data epidemiological detailed with combined phenotypes, obesity of definition better their suggesting weight, obesity. on overall on effect effect by driven mainly is BMI with genes obesity novel many of association the that indicate results GWAS the However, results. compare difficult to it making phenotype, same the chose study every different not traits, include obesity-related did studies some although designs: study the the between to due differences possibly genes, the and phenotype obesity specific a with relationship of To investigate whether different genetic variants from the hypothalamic pathway hypothalamic the from variants genetic different whether investigate To In conclusion, to improve our understanding of obesity pathogenesis, we need a need we pathogenesis, obesity of understanding our improve to conclusion, In t /hipcircumf Central obesity: wais h rltosi bten ee fo te yohlmc ahas n obesity- and pathways hypothalamic the from genes between relationship The t-hip rao erences, ) CAR NMU T, INSR, K GHSR,HTR2A, , NP Y, NPY2R NPY5R, POMC, PTER, SCG3, TMEM18 BDNF CTD15, MCHR2,MTMR9,NE , CRHR1,GAD2,HTR1B (BMI, bodyweight) Figure 3 Figure Overall obesity LEPR, MC4R, NMB GCGR, FT TUB UBL5 ,SH2B1, O, ). The analysis revealed no obvious pattern pattern obvious no revealed analysis The ). AG , HTR2C, MC3R, MC5R GR1, NPC1, CCKAR RP , GNPD A2, subcut (body fat,%body lean bodymasse Body composion aneous fat,fatmass, tc.) suggest using a similar approach in genetic studies of obesity. of studies genetic in approach similar a using suggest We control. appetite of processes the in involved mechanisms signaling neuropeptide counter-regulatory or compensatory involves it since strategy efficient more a be may (166,167). This drug was approach to pharmacotherapy suggested improve anti-obesity a combination as well as account into pathways takes feeding neuronal the of that complexity the analysis network Recently, 165). (164, diseases the these unravel of to etiology needed complex are incorporated, be can interactions order higher even and gene-environment, gene-gene, which in approaches, pathway-based and tools analysis that multi-locus in has a resulted recognition insight growing This of 163). the trait (162, development to contribute to likely are interactions traits, gene-environment and complex gene-gene In association. of model underlying correct the on based be not may methods locus single present, be to need expenditure and intake energy in imbalance Given (161). the of complexity the system and the fact that both andgenetic variation an ytm no con. hs a b dn b ntok nlss mlilcs ol, and tools, multi-locus analysis, network by done be can This account. into system association genetic in issues methodological of hypothalamic the take complexity the should studies future that we propose studies, the all from Apart genes. candidate candidate by promising other many on open However,is still verdict the studies. highlighted functional and gene further is genes these of some of importance The obesity. common of architecture genetic the in homeostasis energy and intake food regulating in pathways hypothalamic the for role key a suggest studies association genome-wide by genes obesity novel of far,discoveries So phenotypes. obesity of development the in important are status metabolic reflecting signals peripheral the integrate and sense that pathways hypothalamic different the in variation genetic that shows review This Conclusions as χ such methods, locus single on focus still obesity as such traits to complex (160). etiology obesity in system whole a as pathways hypothalamic the of role the understand to genes between interactions or epistasis analyze to essential therefore is it and (9), gene another of expression altered by compensated be probably will system this in gene one in function of loss Thus, required. is mechanism a compensatory strong circuits, neuronal its of regulation proper the protect To balance. that energy system regulates physiological complex highly a is hypothalamus the above, discussed As issues Methodological Current statistical strategies to analyze the association of gene variants in relation relation in variants gene of association the analyze to strategies statistical Current 2 statistics statistics 59 Chapter 2 Genetic variation in the hypothalamic pathways and its role on obesity 60 Chapter 2 Genetic variation in the hypothalamic pathways and its role on obesity and pharmaceutical agents that specifically target these pathways. these target specifically that agents pharmaceutical and strategies prevention develop help may knowledge this and obesity of etiology the in role important an play pathways hypothalamic the from genes that shown clearly have We studied. phenotypes obesity specific the defining to paid be also should attention More into factors account. risk take can also system, but environmental this from genes the between interactions the incorporate only not which approaches, pathway-based 1. References 2. 3. 4. 5. 6. 7. 8. 9. 22. 21. 20. 19. 18. 17. 16. 15. 14. 13. 12. 11. 10.

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Weight Loss. Obesity (Silver Spring). 2008; 16: 1969-72. 16: 2008; Spring). (Silver Obesity Loss. and Weight Fat, Ectopic Distribution, Fat Body Whole on Gene FTO the in Variation of Impact A. Fritsche N,Stefan K, MachicaoO, J, SchickF,Kirchhoff Tschritter HU, C, Machann Haring F, Thamer A, Haupt 2189. - 2187 16: 2008; Spring). (Silver Obesity Population. of FTO Korean a in BMI on Effects Polymorphisms Genetic of Replication HD. JY,Shin Kim JR, Kim BL, Park KS, Kim SM, SW,Choi Cha 2857. - 2851 57: 2008; Diabetes. Singapore. in populations Malay and Chinese the in obesity with associated are variants T, Aung OT, WT,CS, Tai Kai Yin FTORick SM, CK, ES. X, Saw Sim Seng M, TanSeielstad JT, R, Dorajoo 393. - 390 70: 2009; (Oxf). M, Endocrinol Clin Spain. from Perez-Barba MJ, Martinez-Calatrava MT, M. Variant Serrano-Rios in rs9939609 Martinez-Larrad the FTO gene is with in obesity associated an adult population C, Zabena JL, Gonzalez-Sanchez 2008; Diabetes. Test. 3151. - 3145 Functional 57: and Studies Cohort Two in Analyses Longitudinal Obesity: with Qi FTO L, Kang K, C, Zhang van Dam RM, Kraft the P,Hunter D,LeeCH, Hu FB.FTO of Gene Is Associated Variant effect the 95-101. 57: 2008; Diabetes. accentuates accumulation. fat body on activity polymorphism rs9939609 physical Low T. Hansen O, Pedersen T, Jorgensen L, T,Hansen Lauritzen A, Sandbaek JO, Clausen SS, Rasmussen K, Borch-Johnsen A, Nielsen Albrechtsen G, AL, Andersen L, Wegner SS, Torekov MS, Mogensen KL, Stender-Petersen CH, Andreasen and controls 4. 9: 2008; cases, Genet. Med BMC in pairs. sister obesity discordant extremely extreme with associated SNPs gene FTO H. Zhao WD, Li RA, Price 791-5. 57: 2008; Diabetes. population. Japanese a in diabetes 2 type to susceptibility with KCNJ11 and SLC30A8, HHEX, CDKN2A/B, IGF2BP2, CDKAL1, of Association S. Y, Maeda Nakamura R, Kawamori K, Kaku A, Kashiwagi H, Hirose A, Y,TanakaTakahashi S, Omori 41. discussion 235-40; 143: 2008; Surg. Arch variants. allelic INSIG2 and FTO with obesity morbid of Association GS. Gerhard CD, Still BenottiP, D, WF,Carey W, Stewart Krum MA, YeagerC, Blosky S, Hartman Wood M, GC, Al-Agha K, Derr H, Gerst M, Susek R, Erdman X, Chu rs9939609 FTO the 5. 7: Cardiovasc 2008; between Diabetol. sample. multi-ethnic Association non-Caucasian a RA. in syndrome Hegele metabolic Harris the MW, and B, polymorphism Huff Zinman PW, S, Yusuf Connelly SS, AJ, Anand P, Hanley Bjerregaard TK, SB, Young MR, Ban RL, Pollex SA, Al-Attar 904. - 902 16: 2008; Spring). (Silver Obesity BMI. With Gene FTO the of Association TD. Adams PN, SP, Hopkins Iadonato CL, Magness CA, Y, Xin Scherer S, Stone SC, Hunt 481-4. 93: 2008; Metab. Genet Mol population. Belgian the in obesity common with associated are gene FTO the W.in Variants Hul VanP, P,L, Roevens Peeters Gaal A, Van Verrijken S, Beckers A, Peeters 1147-50. 57: 2008; Diabetes. Study. Family Quebec the in rate metabolic resting and JC. levels, Engert leptin MC, sensitivity, insulin Vohl adiposity, L, influence FTO of Perusse C, variants Genetic Bouchard A, Montpetit A, Belisle K, Desbiens SD, Bailey R, Do 476-82. 368: 2008; Commun. Res Biophys Biochem phenotypes. related obesity and obesity with children obese severely among variant gene of FTO association in difference gender Major R. Fredriksson HB, Schioth C, Marcus U, Gyllensten J, P, V, Klovins Svensson Danielsson JA, Jacobsson 840-4. 39: 2007; Res. Metab Horm receptor Germans. in Y2 obesity onset early neuropeptide with gene the (NPY2R) in variants sequence of association No A. Hinney J, Hebebrand T, P, Bettecken Lichtner B, Waldenmaier K, Reichwald A, TT,Scherag Nguyen AK, Wermter HJ, Wang 4664-8. 91: 2006; Metab. Endocrinol Clin J children. in Y prepro-neuropeptide in polymorphism Leu7Pro and weight, intake, T.Nutrient Ronnemaa O, Simell L, Rask-Nissila H, Niinikoski U, Pesonen M, Koulu S, Ruottinen MK, Karvonen 797-800. 88: Nutr. 2008; Clin J Am persons. obese severely in intake dietary with polymorphism V103I receptor melanocortin-4 the of F.Association Kronenberg PN, Hopkins TD, Adams SC, Hunt IM, Heid B, Kollerits M, Pichler 65 Chapter 2 Genetic variation in the hypothalamic pathways and its role on obesity 66 Chapter 2 Genetic variation in the hypothalamic pathways and its role on obesity 100. 99. 98. 97. 96. 95. 94. 93. 92. 91. 90. 89. 88. 101.

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