Dataset Information

Family History as an Important Factor for Stratifying Participants in Genetic Studies of Major Depression.

ABSTRACT: Depression is estimated to affect 350 million people worldwide. The World Mental Health Survey conducted in 17 countries found that, on average, about one in 20 people reported having an episode of depression in the previous year. Although depression has been shown to be moderately heritable by studies conducted in the past, the search for its so-called missing heritability has so far been unsuccessful. The difficulty in identifying common genetic variants predisposing to depression could be due to large sample sizes needed to detect small effects on genetic risk and the heterogeneous nature of major depressive disorder (MDD). The aim of our study was to determine whether there was a connection between a family history of depression in MDD patients and the presence of putative risk variants in the well-studied SLC6A4, COMT and PCLO genes. We analyzed 133 patients with MDD (30.0% with a positive family history for MDD and 70.0% sporadic cases) and compared them to 279 healthy controls. When comparing all the depressed patients to controls, no significant differences in genotype and allele distributions were detected. After stratifying patients according to their family history, the PCLO rs2522833 C allele was shown to be significantly less common in patients with a positive family history (p = 0.001), indicating a possible difference in the genetic structure of MDD between familial and sporadic cases and a less important role of the common genetic risk variants for the development of MDD in familial cases.

SUBMITTER: Zalar B

PROVIDER: S-EPMC6231308 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature

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Family History as an Important Factor for Stratifying Participants in Genetic Studies of Major Depression.

Zalar B B Blatnik A A Maver A A Klemenc-Ketiš Z Z Peterlin B B

Balkan journal of medical genetics : BJMG 20180601 1

Depression is estimated to affect 350 million people worldwide. The World Mental Health Survey conducted in 17 countries found that, on average, about one in 20 people reported having an episode of depression in the previous year. Although depression has been shown to be moderately heritable by studies conducted in the past, the search for its so-called missing heritability has so far been unsuccessful. The difficulty in identifying common genetic variants predisposing to depression could be due ...[more]

PMID: 30425904

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Project description:BackgroundAlthough human longevity tends to cluster within families, genetic studies on longevity have had limited success in identifying longevity loci. One of the main causes of this limited success is the selection of participants. Studies generally include sporadically long-lived individuals, i.e. individuals with the longevity phenotype but without a genetic predisposition for longevity. The inclusion of these individuals causes phenotype heterogeneity which results in power reduction and bias. A way to avoid sporadically long-lived individuals and reduce sample heterogeneity is to include family history of longevity as selection criterion using a longevity family score. A main challenge when developing family scores are the large differences in family size, because of real differences in sibship sizes or because of missing data.MethodsWe discussed the statistical properties of two existing longevity family scores: the Family Longevity Selection Score (FLoSS) and the Longevity Relatives Count (LRC) score and we evaluated their performance dealing with differential family size. We proposed a new longevity family score, the mLRC score, an extension of the LRC based on random effects modeling, which is robust for family size and missing values. The performance of the new mLRC as selection tool was evaluated in an intensive simulation study and illustrated in a large real dataset, the Historical Sample of the Netherlands (HSN).ResultsEmpirical scores such as the FLOSS and LRC cannot properly deal with differential family size and missing data. Our simulation study showed that mLRC is not affected by family size and provides more accurate selections of long-lived families. The analysis of 1105 sibships of the Historical Sample of the Netherlands showed that the selection of long-lived individuals based on the mLRC score predicts excess survival in the validation set better than the selection based on the LRC score .ConclusionsModel-based score systems such as the mLRC score help to reduce heterogeneity in the selection of long-lived families. The power of future studies into the genetics of longevity can likely be improved and their bias reduced, by selecting long-lived cases using the mLRC.

Dataset Information

Family History as an Important Factor for Stratifying Participants in Genetic Studies of Major Depression.

Publications

Family History as an Important Factor for Stratifying Participants in Genetic Studies of Major Depression.

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