Patterns of linkage disequilibrium in the type 2 diabetes gene calpain-10

A UNIFIED FRAMEWORK FOR VARIANCE COMPONENT ESTIMATION WITH SUMMARY STATISTICS IN GENOME-WIDE ASSOCIATION STUDIES

Linear mixed models (LMMs) are among the most commonly used tools for genetic association studies. However, the standard method for estimating variance components in LMMs-the restricted maximum likelihood estimation method (REML)-suffers from several important drawbacks: REML requires individual-level genotypes and phenotypes from all samples in the study, is computationally slow, and produces downward-biased estimates in case control studies. To remedy these drawbacks, we present an alternative framework for variance component estimation, which we refer to as MQS. MQS is based on the method of moments (MoM) and the minimal norm quadratic unbiased estimation (MINQUE) criterion, and brings two seemingly unrelated methods-the renowned Haseman-Elston (HE) regression and the recent LD score regression (LDSC)-into the same unified statistical framework. With this new framework, we provide an alternative but mathematically equivalent form of HE that allows for the use of summary statistics. We provide an exact estimation form of LDSC to yield unbiased and statistically more efficient estimates. A key feature of our method is its ability to pair marginal z-scores computed using all samples with SNP correlation information computed using a small random subset of individuals (or individuals from a proper reference panel), while capable of producing estimates that can be almost as accurate as if both quantities are computed using the full data. As a result, our method produces unbiased and statistically efficient estimates, and makes use of summary statistics, while it is computationally efficient for large data sets. Using simulations and applications to 37 phenotypes from 8 real data sets, we illustrate the benefits of our method for estimating and partitioning SNP heritability in population studies as well as for heritability estimation in family studies. Our method is implemented in the GEMMA software package, freely available at www.xzlab.org/software.html.

Further support for association of the mitochondrial complex I subunit gene NDUFV2 with bipolar disorder

BACKGROUND

The nuclear-encoded mitochondrial complex I subunit gene, NDUFV2, has been implicated in the pathogenesis of bipolar disorder (BD) in Japanese by virtue of association of variants in its promoter with BD and decreased NDUFV2 messenger ribonucleic acid (mRNA) levels in B lymphoblasts (BLCL) in BD patients compared to controls. We sought to determine if these same changes occur in non-Japanese populations and, if so, their relationship to altered basal intracellular Ca(2+) ([Ca(2+)](B)) in BLCL from BD patients.

METHODS

Bipolar disorder patients and healthy subjects included 298 subjects of European Caucasian descent. The 5'-nuclease allelic discrimination TaqMan assay was used to detect selected single nucleotide polymorphisms (SNPs) in promoter, introns and 3'UTR regions, spanning the NDUFV2 gene. NDUFV2 mRNA levels and [Ca(2+)](B) in BLCLs were determined.

RESULTS

The A allele of the NDUFV2 SNP rs1156044 was significantly associated (Bonferroni-corrected) with BD (p = 0.013) but differed in allele (rs1156044 G allele) from that previously reported as associated with BD. There was a trend for elevated BLCL [Ca(2+)](B) associated with SNP rs977581 in BD patients, but NDUFV2 mRNA levels in BLCLs did not differ between patients and controls, nor represented genotypes.

CONCLUSIONS

While genetic variants of NDUFV2 may increase risk for BD, the role of its altered expression and the link to intracellular Ca(2+) abnormalities in BD remains equivocal.

The genetic basis of complex traits: rare variants or "common gene, common disease"?

The goal of the Human Genome Project and the subsequent HapMap Project was to accelerate the pace at which genes for complex human traits were discovered. Elated by the early successes from cloning disease genes for monogenic disorders, the architects of the projects reasoned that complex human diseases were tractable to positional cloning methods. However, a schism emerged in the field, with hot debates regarding two competing hypotheses being publicly waged. These opposing hypotheses pertained to the anticipated allelic spectrum and frequency of disease variants associated with common, complex disease. The common disease, common variant hypothesis (CD/CV) stated that a few common allelic variants could account for the genetic variance in disease susceptibility, whereas the rare variant (CD/RV) hypothesis stated that DNA sequence variation at any gene causing disease could encompass a wide range of possibilities, with the most extreme being that each mutation is only found once in the population. The practical consequence of the debate can be broken into two parts. If the CD/CV hypothesis is true, then application of the positional cloning paradigm to map disease genes would be eminently more feasible, as a common allele would be easier to locate. Conversely, if rare variants cause common disease, then identifying these genetic susceptibility variants would be challenging. Whether a disease is caused by rare or common alleles will have an impact on clinical applications, such as designing prognostic assays, or planning therapeutic interventions; fewer susceptibility alleles will simplify assay design, and the associated reduction in costs would amortize if a universally applicable therapy can be deployed. A current review of the literature suggests that both these hypotheses are correct, depending on the gene and disease examined. Although the controversial debate is revived with the identification of each new disease gene, the time has come to integrate both hypotheses in a manner that best explains biological variation in natural populations. The allelic spectrum of variation in a particular gene may be better explained by one of the two hypotheses but, for a multifactorial trait, a composite encompassing all influential genes needs to be constructed.

Inhaled insulin delivery--where are we now?

Since 1925, when the concept of treating diabetes with inhaled insulin (INH) was originally published, a number of clinical challenges have been resolved through technological advancements. Efforts by pharmaceutical partnerships or individual companies have resulted in the development of both injection-free devices and novel insulin formulations. Four different INH systems are now in phase 3 of clinical development, and several other INH systems are in earlier stages of clinical study. Clinical data consistently demonstrate that INH therapy is comparable to subcutaneous (SC) therapy in improving glycaemic control in patients with either type 1 or type 2 diabetes, generally without greater risk of overall hypoglycaemia. INH is generally well tolerated and appears to be safe. Adverse-event profiles for INH therapies are similar to SC insulin therapy, with the majority of events being reported as being mild to moderate. Long-term safety studies are ongoing, with emphasis on evaluating the impact of INH therapy on pulmonary function and immune responses. Although small, reversible decreases in pulmonary diffusion capacity (DL(co)) and FEV1 have been reported in response to INH, pulmonary function and structure do not appear to be affected in any clinically significant way. While insulin antibodies are increased in INH therapy, these antibodies have not been correlated with haemoglobin A1c (HbA1c), insulin dosage, hypoglycaemia, pulmonary function or adverse events. Nevertheless, properly controlled, long-term studies will best answer any remaining concerns. From the patient's perspective, INH therapy is preferred by the majority of patients over conventional SC insulin therapy. Studies have shown that patients prefer INH therapy, because it provides greater lifestyle flexibility and social acceptability while at the same time avoiding the pain associated with injection. Thus, after more than 80 years during which the injection route has been the only means of administering insulin, patients and physicians may soon avail themselves of another valuable tool in management of diabetes.