BGPT: Author Review: Ole Mors

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Quick Explanation Copied

Ole Mors — evidence-style bibliometric snapshot

From the data provided here, Ole Mors shows a very large publication footprint (OpenAlex match: 919 works) and high citation scale (OpenAlex match: 79055).
The included paper list is strongly concentrated in psychiatric genetics / pharmacogenomics / biomarker work (e.g., CYP2C19/CYP2D6 antidepressant response, GWAS of suicidality, epigenetics twin analyses).
Key scientific strength signal: sustained output and impact across decades; key blind spot risk: psychiatry genetics findings often face replication and effect-size heterogeneity challenges.

Long Explanation

Author Review: Ole Mors

Scientifically critical, evidence-grounded review using ONLY the data you provided in this chat (no extra claims beyond that input).

1) Bibliometric scale (from provided matches)

OpenAlex top match: Works: 919, Cited by: 79055, h-index: 116 (as given in your OpenAlex snippet).

Secondary metrics (your local snippet): h-index: 21, total citations: 1499, paper count: 35 (as given).

Interpretation (skeptical): these are not guaranteed to measure the same underlying corpus; bibliometric systems differ in name disambiguation, deduplication, and coverage. So treat them as consistent-with high impact, not definitive.

2) Visualizing yearly output + citations (provided OpenAlex counts)

Raw yearly series are taken directly from your provided counts_by_year table.

3) Open-access intensity (derived from provided OA counts)

Computed from your series: OA ratio = oa_works_count / works_count. (Where works_count=0, ratio is undefined; none of the provided rows show zero works.)

4) Topic distribution (from your provided topic scores)

These are the topic labels + scores that appeared in your snippet (unitless similarity/importance scores as given).

5) What the provided paper titles suggest about research focus

Pharmacogenomics / drug metabolism: multiple titles explicitly reference CYP2C19/CYP2D6 and antidepressant response (e.g., “Metabolic activity of CYP2C19 and CYP2D6 on antidepressant response…”).
Psychiatric genetics (GWAS/meta-analysis): titles include GWAS/meta-analysis of suicide attempt, depression response, and genetic risk loci.
Multi-omics-ish genetics: there is at least one explicit epigenome-wide association study title and at least one title explicitly referencing blood mRNA biomarkers.
Neurodevelopmental / psychiatric susceptibility: older linkage/candidate-locus era titles appear for bipolar disorder/schizophrenia.

Skeptical caution: titles alone cannot establish methodological rigor (e.g., whether analyses controlled for population stratification, multiple testing properly, used replication cohorts, performed sensitivity analyses, or provided reproducible pipelines). Title signals should be treated as hypothesis about focus, not evidence of quality.

6) Evidence-weighted critique (using only what we can infer from the provided titles)

Likely strengths (signals)

Scale + synthesis orientation: the presence of meta-analysis and multi-study genotype imputation language suggests attempts at aggregating evidence across cohorts.
Biological plausibility attempts: drug metabolism genes (e.g., CYP2C19/CYP2D6) provide a mechanistic bridge between genotype and drug response.

Key methodological blind spots & failure modes (generic but relevant to this title pattern)

Small effects & heterogeneity: psychiatric genetics often yields modest effect sizes that can vary across cohorts and sub-phenotypes.
Multiple testing & overfitting risk: high-dimensional association studies frequently face false positives if correction/validation is weak.
Imputation and ancestry structure: genotype imputation accuracy and population stratification can materially change results.
Publication bias / winner’s curse: significant loci are more likely to be reported than null findings.

Confidence note: these are risk categories consistent with the general structure implied by the titles, but your provided input does not include the full text, effect sizes, replication outcomes, or statistical methods—so I cannot verify whether these risks were handled well.

Contradictions to look for (what could disprove a “consistent mechanistic story”)

Findings that do not replicate across datasets or fail in independent imputed-genotype quality regimes.
Effect directions that reverse when adjusting covariates or when using alternative phenotype definitions.
Genetic predictors that explain little variance and are unstable to resampling.

7) Included paper list: structured review table (title-level only)

This table is derived directly from the titles you provided. No DOI/abstract-level methodological claims are made.

Paper title (as provided)
Correction: Metabolic activity of CYP2C19 and CYP2D6 on antidepressant response from 13 clinical studies using genotype imputation: a meta-analysis
Metabolic activity of CYP2C19 and CYP2D6 on antidepressant response from 13 clinical studies using genotype imputation: a meta-analysis
Optimizing the Prediction of Depression Remission: A Longitudinal Machine Learning Approach
GWAS Meta-Analysis of Suicide Attempt: Identification of 12 Genome-Wide Significant Loci and Implication of Genetic Risks for Specific Health Factors.
Apr 27, 2021 FUT2–ABO epistasis increases the risk of early childhood asthma and Streptococcus
Antidepressant Response in Major Depressive Disorder: A Genome-wide Association Study
Epigenome-wide association study of depression symptomatology in elderly monozygotic twins
Infections and exposure to anti‐infective agents and the risk of severe mental disorders: a nationwide study
New insights on the pharmacogenomics of antidepressant response from the GENDEP and STAR*D studies: rare variant analysis and high-density imputation
Investigation of blood mRNA biomarkers for suicidality in an independent sample
Genome-wide study of association and interaction with maternal cytomegalovirus infection suggests new schizophrenia loci
The norepinephrine transporter gene is a candidate gene for panic disorder
Interaction between serotonin transporter gene variants and life events predicts response to antidepressants in the GENDEP project
Trans-diagnostic outcome of eating disorders: A 30-month follow-up study of 629 patients.
P.3.010 CYP2D6 and CYP2C19 genotypes predict antidepressant dose in the GENDEP project
Genome-wide association study of increasing suicidal ideation during antidepressant treatment in the GENDEP project
P.3.13 Temperament and character of subjects with treatment increase suicidal ideations in the GENDEP study
Depression, Migraine With Aura and Migraine Without Aura: Their Familiality and Interrelatedness
Genetic association data from GENDEP, a multicentre European Study
Evidence implicating BRD1 with brain development and susceptibility to both schizophrenia and bipolar affective disorder
Association analyses suggest GPR24 as a shared susceptibility gene for bipolar affective disorder and schizophrenia
Joint multi‐population analysis for genetic linkage of bipolar disorder or “wellness” to chromosome 4p
No association between a neuronal nitric oxide synthase (NOS1) gene polymorphism on chromosome 12q24 and bipolar disorder
Possible evidence for a common risk locus for bipolar affective disorder and schizophrenia on chromosome 4p16 in patients from the Faroe Islands
Is head injury a risk factor for schizophrenia?
Decreased risk of acute appendicitis in patients with schizophrenia or manic-depressive psychosis.
A haplotype-based study of lithium responding patients with bipolar affective disorder on the Faroe Islands.
A population-based register study of the association between schizophrenia and rheumatoid arthritis.
Support for the possible locus on chromosome 4p16 for bipolar affective disorder
A functional variant of the serotonin transporter gene in families with bipolar affective disorder.
Susceptibility loci for bipolar affective disorder on chromosome 18? A review and a study of Danish families
Linkage study between manic-depressive illness and chromosome 21.
A possible locus for manic depressive illness on chromosome 16p13
Linkage analysis between manic-depressive illness and the region on chromosome 15q involved in Prader-Willi syndrome, including two GABAA receptor subtype genes.

8) Bottom-line scientific assessment (what we can and cannot conclude)

Known from provided data: Very high publication/citation scale (as given), strong topic association with medicine/biology/genetics/psychiatry, and a visible research focus spanning psychiatric genetics, pharmacogenomics, and some biomarker/epigenetic studies (title signals).

Not known from provided data: statistical rigor details (QC thresholds, covariate structure), replication status, effect sizes/credible intervals, model calibration, heterogeneity analyses, pre-registration, data/code availability, and any independent verification.

Scientific confidence: Moderate for “what they work on and scale of impact”; low-to-moderate for “how rigorous each result is,” because the chat input contains titles/metrics only, not methods or results.

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Updated: April 07, 2026