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Landen, M.

Publications and source records attributed to Landen, M..

2 recordsLinked to original sources

Effect of Alcohol and Cocaine Abuse on Neuronal and Non-Neuronal Cell Turnover in the Adult Human Hippocampus

Clinical studies on humans with a history of chronic abuse of alcohol or cocaine show cognitive impairments associated with hippocampal atrophy. Adult hippocampal neurogenesis is a process important for memory formation and has been shown to be impaired by alcohol and cocaine in rodent models. It has thus been suggested that a reduction in adult neurogenesis may contribute to cognitive dysfunctions seen in patients with abuse. In addition, reduced adult neurogenesis has been suggested to play a role in the pathology of addiction vulnerability. We have previously demonstrated persistent adult hippocampal neurogenesis throughout life by measuring 14C concentrations in genomic DNA, incorporated during cell division, in a mixed cohort of subjects. In this study, we use the same strategy to assess the extent of cell turnover of neuronal and non-neuronal cells in the hippocampus of humans with known history of alcohol and cocaine abuse and compare these with healthy controls. We find that there is significant neuronal and non-neuronal turnover in healthy controls, as well as in individuals with long term alcohol use orcocaine use. Using mathematical modelling, we compare the extent of cell turnover of neurons and non-neuronal cells and did not find any significant difference between healthy controls and the two addiction groups. While we cannot exclude scenarios of altered adult neurogenesis over shorter periods of time, our data does not support the theory of low neurogenesis as a mechanism of addiction vulnerability.

neuroscience↗

Genetic validation of bipolar disorder identified by automated phenotyping using electronic health records

Bipolar disorder (BD) is a heritable mood disorder characterized by episodes of mania and depression. Although genomewide association studies (GWAS) have successfully identified genetic loci contributing to BD risk, sample size has become a rate-limiting obstacle to genetic discovery. Electronic health records (EHRs) represent a vast but relatively untapped resource for high-throughput phenotyping. As part of the International Cohort Collection for Bipolar Disorder (ICCBD), we previously validated automated EHR-based phenotyping algorithms for BD against in-person diagnostic interviews (Castro et al. 2015). Here, we establish the genetic validity of these phenotypes by determining their genetic correlation with traditionally-ascertained samples. Case and control algorithms were derived from structured and narrative text in the Partners Healthcare system comprising more than 4.6 million patients over 20 years. Genomewide genotype data for 3,330 BD cases and 3,952 controls of European ancestry were used to estimate SNP-based heritability (h2g) and genetic correlation(rg) between EHR-based phenotype definitions and traditionally-ascertained BD cases in GWAS by the ICCBD and Psychiatric Genomics Consortium (PGC) using LD score regression. We evaluated BD cases identified using 4 EHR-based algorithms: an NLP-based algorithm (95-NLP) and 3 rule-based algorithms using codified EHR with decreasing levels of stringency - \"coded-strict\", \"coded-broad\", and \"coded-broad based on a single clinical encounter\" (coded-broad-SV). The analytic sample comprised 862 95-NLP, 1,968 coded-strict, 2,581 coded-broad, 408 coded-broad-SV BD cases, and 3,952 controls. The estimated h2g were 0.24 (p=0.015), 0.09 (p=0.064), 0.13 (p=0.003), 0.00 (p=0.591) for 95-NLP, coded-strict, coded-broad and coded-broad-SV BD, respectively. The h2g for all EHR-based cases combined except coded-broad-SV (excluded due to 0 h2g) was 0.12 (p=0.004). These h2g were lower or similar to the h2g observed by the ICCBD+PGCBD (0.23, p=3.17E-80, total N=33,181). However, the rg between ICCBD+PGCBD and the EHR-based cases were high for 95-NLP (0.66, p=3.69x10-5), coded-strict (1.00, p=2.40x10-4), and coded-broad (0.74, p=8.11x10-7). The rg between EHR-based BDs ranged from 0.90 to 0.98. These results provide the first genetic validation of automated EHR-based phenotyping for BD and suggest that this approach identifies cases that are highly genetically correlated with those ascertained through conventional methods. High throughput phenotyping using the large data resources available in EHRs represents a viable method for accelerating psychiatric genetic research.

genetics↗