Okbay A, Baselmans BM, De Neve JE, Turley P, Nivard MG,
Fontana MA, Meddens
SF, Linnér RK, Rietveld CA, Derringer J, Gratten J, Lee JJ,
Liu JZ, de Vlaming R,
Ahluwalia TS, Buchwald J, Cavadino A, Frazier-Wood AC,
Furlotte NA, Garfield V,
Geisel MH, Gonzalez JR, Haitjema S, Karlsson R, van der Laan
SW, Ladwig KH, Lahti
J, van der Lee SJ, Lind PA, Liu T, Matteson L, Mihailov E,
Miller MB, Minica CC,
Nolte IM, Mook-Kanamori D, van der Most PJ, Oldmeadow C,
Qian Y, Raitakari O,
Rawal R, Realo A, Rueedi R, Schmidt B, Smith AV,
Stergiakouli E, Tanaka T, Taylor
K, Wedenoja J, Wellmann J, Westra HJ, Willems SM, Zhao W;
LifeLines Cohort Study,
Amin N, Bakshi A, Boyle PA, Cherney S, Cox SR, Davies G,
Davis OS, Ding J, Direk
N, Eibich P, Emeny RT, Fatemifar G, Faul JD, Ferrucci L,
Forstner A, Gieger C,
Gupta R, Harris TB, Harris JM, Holliday EG, Hottenga JJ, De
Jager PL, Kaakinen
MA, Kajantie E, Karhunen V, Kolcic I, Kumari M, Launer LJ,
Franke L, Li-Gao R,
Koini M, Loukola A, Marques-Vidal P, Montgomery GW, Mosing
MA, Paternoster L,
Pattie A, Petrovic KE, Pulkki-Råback L, Quaye L, Räikkönen
K, Rudan I, Scott RJ,
Smith JA, Sutin AR, Trzaskowski M, Vinkhuyzen AE, Yu L,
Zabaneh D, Attia JR,
Bennett DA, Berger K, Bertram L, Boomsma DI, Snieder H,
Chang SC, Cucca F, Deary
IJ, van Duijn CM, Eriksson JG, Bültmann U, de Geus EJ,
Groenen PJ, Gudnason V,
Hansen T, Hartman CA, Haworth CM, Hayward C, Heath AC, Hinds
DA, Hyppönen E,
Iacono WG, Järvelin MR, Jöckel KH, Kaprio J, Kardia SL,
Keltikangas-Järvinen L,
Kraft P, Kubzansky LD, Lehtimäki T, Magnusson PK, Martin NG,
McGue M, Metspalu A,
Mills M, de Mutsert R, Oldehinkel AJ, Pasterkamp G, Pedersen
NL, Plomin R,
Polasek O, Power C, Rich SS, Rosendaal FR, den Ruijter HM,
Schlessinger D,
Schmidt H, Svento R, Schmidt R, Alizadeh BZ, Sørensen TI,
Spector TD, Steptoe A,
Terracciano A, Thurik AR, Timpson NJ, Tiemeier H,
Uitterlinden AG, Vollenweider
P, Wagner GG, Weir DR, Yang J, Conley DC, Smith GD, Hofman
A, Johannesson M,
Laibson DI, Medland SE, Meyer MN, Pickrell JK, Esko T,
Krueger RF, Beauchamp JP,
Koellinger PD, Benjamin DJ, Bartels M, Cesarini D. Genetic
variants associated
with subjective well-being, depressive symptoms, and
neuroticism identified
through genome-wide analyses. Nat Genet. 2016 Jun;48(6):624-33.
Abstract
Very few genetic variants have been associated with
depression and neuroticism, likely because of limitations on sample size in
previous studies. Subjective well-being, a phenotype that is genetically
correlated with both of these traits, has not yet been studied with genome-wide
data. We conducted genome-wide association studies of three phenotypes:
subjective well-being (n = 298,420), depressive symptoms (n = 161,460), and
neuroticism (n = 170,911). We identify 3 variants associated with subjective
well-being, 2 variants associated with depressive symptoms, and 11 variants
associated with neuroticism, including 2 inversion polymorphisms. The two loci
associated with depressive symptoms replicate in an independent depression
sample. Joint analyses that exploit the high genetic correlations between the
phenotypes (|ρ^| ≈ 0.8) strengthen the overall credibility of the findings and
allow us to identify additional variants. Across our phenotypes, loci
regulating expression in central nervous system and adrenal or pancreas tissues
are strongly enriched for association.
________________________________________________________________________
From the article
Subjective well-being—as measured by survey questions on
life satisfaction, positive affect, or happiness—is a major topic of research
in psychology, economics, and epidemiology. Twin studies have found that
subjective well-being is genetically correlated with depression (characterized
by negative affect, anxiety, low energy, bodily aches and pains, pessimism, and
other symptoms) and neuroticism (a personality trait characterized by easily
experiencing negative emotions such as anxiety and fear). Depression and
neuroticism have received much more attention than subjective well-being in
genetic association studies, but the discovery of genetic variants associated
with either of them has proven elusive.
Here we report a series of separate and joint analyses of
subjective well-being, depressive symptoms, and neuroticism, which identify 16
genome-wide significant associations across the three phenotypes. In our two
joint analyses, we exploit the high genetic correlation between subjective
well-being, depressive symptoms, and neuroticism (i) to evaluate the
credibility of the associations from our initial genome-wide association study
(GWAS) and (ii) to identify new associations (beyond those identified by the
GWAS)...
We found significant enrichment of central nervous system
for all three phenotypes and, perhaps more surprisingly, enrichment of
adrenal/pancreas for subjective well-being and depressive symptoms. The cause
of the adrenal/pancreas enrichment is unclear, but we note that the adrenal
glands produce several hormones, including cortisol, epinephrine, and
norepinephrine, known to have important roles in the bodily regulation of mood
and stress. It has been robustly found that blood serum levels of cortisol in
patients afflicted by depression are elevated relative to those in controls.
Genetics of Personality Consortium, de Moor MH, van den Berg SM, Verweij KJ,Krueger RF, Luciano M, Arias Vasquez A, Matteson LK, Derringer J, Esko T, Amin N, Gordon SD, Hansell NK, Hart AB, Seppälä I, Huffman JE, Konte B, Lahti J, Lee M, Miller M, Nutile T, Tanaka T, Teumer A, Viktorin A, Wedenoja J, Abecasis GR, Adkins DE, Agrawal A, Allik J, Appel K, Bigdeli TB, Busonero F, Campbell H, Costa PT, Davey Smith G, Davies G, de Wit H, Ding J, Engelhardt BE, Eriksson JG, Fedko IO, Ferrucci L, Franke B, Giegling I, Grucza R, Hartmann AM, Heath AC, Heinonen K, Henders AK, Homuth G, Hottenga JJ, Iacono WG, Janzing J, Jokela M, Karlsson R, Kemp JP, Kirkpatrick MG, Latvala A, Lehtimäki T, Liewald DC, Madden PA, Magri C, Magnusson PK, Marten J, Maschio A, Medland SE, Mihailov E, Milaneschi Y, Montgomery GW, Nauck M, Ouwens KG, Palotie A, Pettersson E, Polasek O, Qian Y, Pulkki-Råback L, Raitakari OT, Realo A, Rose RJ, Ruggiero D, Schmidt CO, Slutske WS, Sorice R, Starr JM, St Pourcain B, Sutin AR, Timpson NJ, Trochet H, Vermeulen S, Vuoksimaa E, Widen E, Wouda J, Wright MJ, Zgaga L, Porteous D, Minelli A, Palmer AA, Rujescu D, Ciullo M, Hayward C, Rudan I, Metspalu A, Kaprio J, Deary IJ, Räikkönen K, Wilson JF, Keltikangas-Järvinen L, Bierut LJ, Hettema JM, Grabe HJ, van Duijn CM, Evans DM, Schlessinger D, Pedersen NL, Terracciano A, McGue M, Penninx BW, Martin NG, Boomsma DI. Meta-analysis of Genome-wide Association Studies for Neuroticism, and the Polygenic Association With Major Depressive
ReplyDeleteDisorder. JAMA Psychiatry. 2015 Jul;72(7):642-50. (Continued)
(continued)
ReplyDeleteAbstract
IMPORTANCE:
Neuroticism is a pervasive risk factor for psychiatric conditions. It genetically overlaps with major depressive disorder (MDD) and is therefore an important phenotype for psychiatric genetics. The Genetics of Personality Consortium has created a resource for genome-wide association analyses of personality traits in more than 63,000 participants (including MDD cases).
OBJECTIVES:
To identify genetic variants associated with neuroticism by performing a meta-analysis of genome-wide association results based on 1000 Genomes imputation; to evaluate whether common genetic variants as assessed by single-nucleotide polymorphisms (SNPs) explain variation in neuroticism by estimating SNP-based heritability; and to examine whether SNPs that predict neuroticism also predict MDD.
DESIGN, SETTING, AND PARTICIPANTS:
Genome-wide association meta-analysis of 30 cohorts with genome-wide genotype, personality, and MDD data from the Genetics of Personality Consortium. The study included 63,661 participants from 29 discovery cohorts and 9786 participants from a replication cohort. Participants came from Europe, the United States, or Australia. Analyses were conducted between 2012 and 2014.
MAIN OUTCOMES AND MEASURES:
Neuroticism scores harmonized across all 29 discovery cohorts by item response theory analysis, and clinical MDD case-control status in 2 of the cohorts.
RESULTS:
A genome-wide significant SNP was found on 3p14 in MAGI1 (rs35855737; P = 9.26 × 10-9 in the discovery meta-analysis). This association was not replicated (P = .32), but the SNP was still genome-wide significant in the meta-analysis of all 30 cohorts (P = 2.38 × 10-8). Common genetic variants explain 15% of the variance in neuroticism. Polygenic scores based on the meta-analysis of neuroticism in 27 cohorts significantly predicted neuroticism (1.09 × 10-12 < P < .05) and MDD (4.02 × 10-9 < P < .05) in the 2 other cohorts.
CONCLUSIONS AND RELEVANCE:
This study identifies a novel locus for neuroticism. The variant is located in a known gene that has been associated with bipolar disorder and schizophrenia in previous studies. In addition, the study shows that neuroticism is influenced by many genetic variants of small effect that are either common or tagged by common variants. These genetic variants also influence MDD. Future studies should confirm the role of the MAGI1 locus for neuroticism and further investigate the association of MAGI1 and the polygenic association to a range of other psychiatric disorders that are phenotypically correlated with neuroticism.
Ware EB, Mukherjee B, Sun YV, Diez-Roux AV, Kardia SL, Smith JA. Comparative genome-wide association studies of a depressive symptom phenotype in a repeated measures setting by race/ethnicity in the Multi-Ethnic Study of Atherosclerosis. BMC Genet. 2015 Oct 12;16:118.
ReplyDeleteAbstract
BACKGROUND:
Time-varying phenotypes have been studied less frequently in the context of genome-wide analyses across ethnicities, particularly for mood disorders. This study uses genome-wide association studies of depressive symptoms in a longitudinal framework and across multiple ethnicities to find common variants for depressive symptoms. Ethnicity-specific GWAS for depressive symptoms were conducted using three approaches: a baseline measure, longitudinal measures averaged over time, and a repeated measures analysis. We then used meta-analysis to jointly analyze the results across ethnicities within the Multi-ethnic Study of Atherosclerosis (MESA, n = 6,335), and then within ethnicity, across MESA and a sample from the Health and Retirement Study African- and European-Americans (HRS, n = 10,163).
METHODS:
This study uses genome-wide association studies of depressive symptoms in a longitudinal framework and across multiple ethnicities to find common variants for depressive symptoms. Ethnicity-specific GWAS for depressive symptoms were conducted using three approaches: a baseline measure, longitudinal measures averaged over time, and a repeated measures analysis. We then used meta-analysis to jointly analyze the results across ethnicities within the Multi-ethnic Study of Atherosclerosis (MESA, n = 6,335), and then within ethnicity, across MESA and a sample from the Health and Retirement Study African- and European-Americans (HRS, n = 10,163).
RESULTS:
Several novel variants were identified at the genome-wide suggestive level (5×10(-8) < p-value ≤ 5×10(-6)) in each ethnicity for each approach to analyzing depressive symptoms. The repeated measures analyses resulted in typically smaller p-values and an increase in the number of single-nucleotide polymorphisms (SNP) reaching genome-wide suggestive level.