Estimating the NIH Efficient Frontier

Background: The National Institutes of Health (NIH) is among the world’s largest investors in biomedical research, with a mandate to: “…lengthen life, and reduce the burdens of illness and disability.” Its funding decisions have been criticized as insufficiently focused on disease burden. We hypothesize that modern portfolio theory can create a closer link between basic research and outcome, and offer insight into basic-science related improvements in public health. We propose portfolio theory as a systematic framework for making biomedical funding allocation decisions–one that is directly tied to the risk/reward trade-off of burden-of-disease outcomes. Methods and Findings: Using data from 1965 to 2007, we provide estimates of the NIH “efficient frontier”, the set of funding allocations across 7 groups of disease-oriented NIH institutes that yield the greatest expected return on investment for a given level of risk, where return on investment is measured by subsequent impact on U.S. years of life lost (YLL). The results suggest that NIH may be actively managing its research risk, given that the volatility of its current allocation is 17% less than that of an equal-allocation portfolio with similar expected returns. The estimated efficient frontier suggests that further improvements in expected return (89% to 119% vs. current) or reduction in risk (22% to 35% vs. current) are available holding risk or expected return, respectively, constant, and that 28% to 89% greater decrease in average years-of-life-lost per unit risk may be achievable. However, these results also reflect the imprecision of YLL as a measure of disease burden, the noisy statistical link between basic research and YLL, and other known limitations of portfolio theory itself. Conclusions: Our analysis is intended to serve as a proof-of-concept and starting point for applying quantitative methods to allocating biomedical research funding that are objective, systematic, transparent, repeatable, and expressly designed to reduce the burden of disease. By approaching funding decisions in a more analytical fashion, it may be possible to improve their ultimate outcomes while reducing unintended consequences

Mouse Genome-Wide Association and Systems Genetics Identify Asxl2 As a Regulator of Bone Mineral Density and Osteoclastogenesis

Significant advances have been made in the discovery of genes affecting bone mineral density (BMD); however, our understanding of its genetic basis remains incomplete. In the current study, genome-wide association (GWA) and co-expression network analysis were used in the recently described Hybrid Mouse Diversity Panel (HMDP) to identify and functionally characterize novel BMD genes. In the HMDP, a GWA of total body, spinal, and femoral BMD revealed four significant associations (−log10P>5.39) affecting at least one BMD trait on chromosomes (Chrs.) 7, 11, 12, and 17. The associations implicated a total of 163 genes with each association harboring between 14 and 112 genes. This list was reduced to 26 functional candidates by identifying those genes that were regulated by local eQTL in bone or harbored potentially functional non-synonymous (NS) SNPs. This analysis revealed that the most significant BMD SNP on Chr. 12 was a NS SNP in the additional sex combs like-2 (Asxl2) gene that was predicted to be functional. The involvement of Asxl2 in the regulation of bone mass was confirmed by the observation that Asxl2 knockout mice had reduced BMD. To begin to unravel the mechanism through which Asxl2 influenced BMD, a gene co-expression network was created using cortical bone gene expression microarray data from the HMDP strains. Asxl2 was identified as a member of a co-expression module enriched for genes involved in the differentiation of myeloid cells. In bone, osteoclasts are bone-resorbing cells of myeloid origin, suggesting that Asxl2 may play a role in osteoclast differentiation. In agreement, the knockdown of Asxl2 in bone marrow macrophages impaired their ability to form osteoclasts. This study identifies a new regulator of BMD and osteoclastogenesis and highlights the power of GWA and systems genetics in the mouse for dissecting complex genetic traits

The Neural Basis of Decision-Making and Reward Processing in Adults with Euthymic Bipolar Disorder or Attention-Deficit/Hyperactivity Disorder (ADHD)

Attention-deficit/hyperactivity disorder (ADHD) and bipolar disorder (BD) share DSM-IV criteria in adults and cause problems in decision-making. Nevertheless, no previous report has assessed a decision-making task that includes the examination of the neural correlates of reward and gambling in adults with ADHD and those with BD

The pathophysiology of restricted repetitive behavior

Restricted, repetitive behaviors (RRBs) are heterogeneous ranging from stereotypic body movements to rituals to restricted interests. RRBs are most strongly associated with autism but occur in a number of other clinical disorders as well as in typical development. There does not seem to be a category of RRB that is unique or specific to autism and RRB does not seem to be robustly correlated with specific cognitive, sensory or motor abnormalities in autism. Despite its clinical significance, little is known about the pathophysiology of RRB. Both clinical and animal models studies link repetitive behaviors to genetic mutations and a number of specific genetic syndromes have RRBs as part of the clinical phenotype. Genetic risk factors may interact with experiential factors resulting in the extremes in repetitive behavior phenotypic expression that characterize autism. Few studies of individuals with autism have correlated MRI findings and RRBs and no attempt has been made to associate RRB and post-mortem tissue findings. Available clinical and animal models data indicate functional and structural alterations in cortical-basal ganglia circuitry in the expression of RRB, however. Our own studies point to reduced activity of the indirect basal ganglia pathway being associated with high levels of repetitive behavior in an animal model. These findings, if generalizable, suggest specific therapeutic targets. These, and perhaps other, perturbations to cortical basal ganglia circuitry are mediated by specific molecular mechanisms (e.g., altered gene expression) that result in long-term, experience-dependent neuroadaptations that initiate and maintain repetitive behavior. A great deal more research is needed to uncover such mechanisms. Work in areas such as substance abuse, OCD, Tourette syndrome, Parkinson’s disease, and dementias promise to provide findings critical for identifying neurobiological mechanisms relevant to RRB in autism. Moreover, basic research in areas such as birdsong, habit formation, and procedural learning may provide additional, much needed clues. Understanding the pathophysioloy of repetitive behavior will be critical to identifying novel therapeutic targets and strategies for individuals with autism