Atlas / Deep research

Microcephaly Genomics Literature Map

This page is the research layer that wraps the inherited MCPH heatmap. It asks: what is the current genomic state of the art for primary microcephaly, and how does that Mendelian developmental biology connect to psychiatric, cognitive, cortical, and neurodegenerative disease genetics?

5search engines / metadata sources
26curated anchor papers in this first pass
2026updated through June 17, 2026
2jobs: causal MCPH genes + cross-condition maps
Core thesis question Which MCPH genes are causal, current, and biologically interpretable?

Answered with reviews, cohort sequencing, gene-specific mechanisms, HGNC aliases, PanelApp/G2P/OMIM/ClinGen, and recent functional papers.

Heatmap question Why compare microcephaly genes with psychiatric and cortical disorder genes?

Answered with fetal brain development, neural stem cell expression, cross-disorder GWAS, MPRA, and single-cell regulatory-genomics papers.

Research protocol

How I would run the literature review if this were a thesis chapter.

01

Start from the local scientific object

Use Mario's 33-gene MCPH list, the original bundle databases, the R heatmap, and Mario's Master's thesis bibliography as the seed. This prevents the review from becoming a generic microcephaly essay: every paper must help explain the exact plot, the exact genes, or the exact disease intersections in this project.

02

Normalize names before searching

Search both current and historical symbols: KNL1/CASC5/D40/Blinkin and TRAPPC14/C7orf43/MAP11. Do the same for every MCPH gene with HGNC aliases. Otherwise, the older literature and older databases appear falsely incomplete.

03

Use PubMed for biomedical precision

PubMed is the backbone for curated biomedical metadata: PMID, journal, title, authors, publication year, MeSH-like discoverability, abstracts, and links to PubMed Central where available. The core queries combine primary microcephaly, MCPH, exome/genomics, mechanisms, and each gene symbol.

04

Use Google Scholar for citation chasing

Google Scholar is excellent for "cited by" exploration and locating preprints, theses, conference abstracts, and institutional repositories. I would not scrape it automatically; I would use it manually to check whether anchor papers have newer citing papers not yet obvious in PubMed.

05

Use OpenAlex, Crossref, and Semantic Scholar as reproducible layers

OpenAlex gives citation counts, DOI-normalized metadata, publication venues, and open web identifiers. Crossref is useful for DOI verification. Semantic Scholar is useful for topic-sensitive relevance and citation neighborhoods. These do not replace reading papers; they make the bibliography traceable.

06

Use Connected Papers for conceptual topology

For visual mapping, seed Connected Papers with one recent anchor paper, especially Mato-Blanco et al. 2025 on neural stem cells and cortical disorders, then separately with Phan and Holland 2021 or Zaqout and Kaindl 2022 for MCPH mechanisms. The graph should guide reading clusters, not replace source evaluation.

07

Separate causal evidence from intersection evidence

MCPH gene causality comes from families, exome/genome sequencing, biallelic variant interpretation, model systems, and clinical gene-disease validity. Psychiatric or cognitive intersections usually come from common-variant GWAS, gene-set enrichment, fetal brain expression, chromatin accessibility, MPRA, and single-cell annotations.

08

Rank papers by thesis utility

A paper can be important because it is highly cited, very recent, directly about one of our confusing genes, or methodologically close to the heatmap. The bibliography below labels each paper by role so we do not confuse popularity with relevance.

First synthesis

The field is converging on one big idea: small brains are often progenitor problems.

Primary microcephaly is not simply "a list of genes that make the head small." The most coherent modern view is that many MCPH genes are dosage-sensitive components of the machinery that lets neural stem and progenitor cells expand safely before they generate neurons. Centrosomes, centrioles, kinetochores, spindle orientation, DNA repair, RNA processing, chromatin state, cilia, and cell-cycle timing all matter because early cortical growth is an amplification problem: a small change in progenitor survival, mitotic timing, or symmetric/asymmetric division can produce a large change in final neuron number.

This is why Gabriel Santpere's developmental-genomics line is so relevant to the old heatmap. The inherited plot is asking whether genes selected from one developmental phenotype, microcephaly, occupy biologically meaningful positions in fetal progenitor expression and in other disease gene sets. The modern version of that question should not only count intersections; it should ask when the genes are active, which progenitor states they perturb, which mechanisms they share, and which disease categories are genuinely connected rather than merely sharing broad neurodevelopmental vocabulary.

Lane A: define MCPH genes

Reviews and cohort papers establish the causal landscape, inheritance patterns, core mechanisms, and the difference between classic MCPH genes and syndromic/candidate microcephaly genes.

Lane B: explain KNL1/CASC5

The KNL1 alias story is not clerical. It tells us that older databases, older scripts, and current HGNC nomenclature can disagree while referring to the same biological object.

Lane C: connect to progenitors

Human neural stem cell and fetal cortex papers translate gene lists into developmental timing, cell type, chromatin state, and regulatory-network context.

Lane D: connect to psychiatric genomics

Cross-disorder GWAS and MPRA papers show how ASD, ADHD, schizophrenia, bipolar disorder, depression, and other traits share regulatory architecture, often active during fetal brain development.

Gene-by-gene evidence matrix

For each MCPH gene: papers, PanelApp, ClinGen, Open Targets, and live database trails.

This is the bibliographic evidence pass requested after the first literature map. It is generated from public sources on June 17, 2026: PanelApp Severe microcephaly, PubMed, ClinGen gene-disease validity downloads, Open Targets Platform, and direct links to HGNC, G2P, OMIM, and ClinGen searches.

Reasoned bibliography

Curated anchor papers for the next version of the atlas.

Citation-network metadata were checked during curation, but the visible bibliography keeps the paper byline clean: authors, journal, year, DOI, and direct source links.

1. State-of-the-art reviews: what MCPH means biologically

Core review

Time is of the essence: the molecular mechanisms of primary microcephaly

Phan & Holland. Genes & Development, 2021.

This is probably the best conceptual entry point for the thesis because it explains why timing of progenitor expansion, centrosomes, mitosis, and developmental checkpoints are central to MCPH.

Foundational review

The Genetics of Primary Microcephaly

Jayaraman, Bae & Walsh. Annual Review of Genomics and Human Genetics, 2018.

A high-value foundation for classic MCPH genes, cortical development, centrosome/cell-cycle mechanisms, and why brain size is especially sensitive to progenitor biology.

Genetic overview

Dissecting the Genetic and Etiological Causes of Primary Microcephaly

Jean, Stuart & Tarailo-Graovac. Frontiers in Neurology, 2020.

Useful for separating inherited primary microcephaly, secondary/environmental causes, syndromic presentations, and gene discovery logic.

Phenotype expansion

Autosomal Recessive Primary Microcephaly: Not Just a Small Brain

Zaqout & Kaindl. Frontiers in Cell and Developmental Biology, 2022.

Important because it pushes beyond the simplistic idea of MCPH as isolated small brain size and emphasizes broader neurodevelopmental and systemic features.

Centrosome focus

Genetic Primary Microcephalies: When Centrosome Dysfunction Dictates Brain and Body Size

Farcy, Hachour, Bahi-Buisson & Passemard. Cells, 2023.

A focused review for the centrosome/centriole axis, especially useful for interpreting genes such as ASPM, WDR62, CDK5RAP2, CEP135, CEP152, and CENPJ.

DNA repair axis

DNA damage and repair: underlying mechanisms leading to microcephaly

Ribeiro et al. Frontiers in Cell and Developmental Biology, 2023.

Essential for genes whose microcephaly mechanism is genome maintenance rather than only spindle/centrosome biology. It helps frame PNKP, ATR, NBS1-like pathways, and p53-mediated progenitor loss.

2. Recent discovery and mechanism papers: where the field is now

2026 cohort

Expanding the genetic spectrum of autosomal recessive microcephaly in Pakistani families

Ahmad et al. BMC Neurology, 2026. Open access. DOI: 10.1186/s12883-026-05027-9.

Very recent family-based sequencing paper. It is useful for showing that MCPH gene discovery and variant interpretation remain active in consanguineous/founder-enriched populations.

2026 cohort

Elucidating the Genetic Landscape, Phenotypic Spectrum, and Pathogenic Mechanisms in a Turkish Cohort with Primary Microcephaly

Tüysüz et al. Clinical Genetics, 2026. DOI: 10.1111/cge.70182.

Important because a cohort design can distinguish frequent, rare, syndromic, and candidate mechanisms better than a single-family report. This should be checked closely for genes overlapping Mario's list.

2026 mechanism

Distinct pathophysiological mechanisms of CEP152 variants in microcephaly and brain abnormalities

Hamada et al. EMBO Molecular Medicine, 2026. DOI: 10.1038/s44321-026-00427-3.

Strong example of why two variants in the same gene can produce different developmental consequences. This is a good model for the atlas gene profiles: gene name alone is not enough.

New gene/mechanism

EXOSC10 haploinsufficiency causes primary microcephaly by derepression of Sonic hedgehog signalling

Ulmke et al. Brain, 2025/2026 issue. DOI: 10.1093/brain/awaf405.

Valuable because it extends the mechanistic vocabulary beyond the classic centrosome list into RNA exosome biology and Sonic hedgehog signalling. It should be considered when deciding whether Mario's list is "MCPH only" or broader microcephaly.

3. KNL1 / CASC5 lineage: the alias problem becomes biology

Original CASC5 link

Kinetochore KMN network gene CASC5 mutated in primary microcephaly

Genin et al. Human Molecular Genetics, 2012.

This is the key origin paper for CASC5/KNL1 as an MCPH gene. It explains why the old bundle contains CASC5 while current HGNC terminology points us to KNL1.

Variant expansion

A novel homozygous splicing mutation of CASC5 causes primary microcephaly in a large Pakistani family

Szczepanski et al. Human Genetics, 2015.

Useful for showing that the CASC5/KNL1 association is not a one-family curiosity and that splicing/disrupted kinetochore function is a recurrent mechanism.

Disease model

Microcephaly Modeling of Kinetochore Mutation Reveals a Brain-Specific Phenotype

Omer et al. Cell Reports, 2018.

This paper is especially educational: it asks why a general mitotic/kinetochore component can produce a brain-predominant phenotype, which is one of the central puzzles of MCPH biology.

Mouse genetics

Robust elimination of genome-damaged cells safeguards against brain somatic aneuploidy following Knl1 deletion

Shi et al. Nature Communications, 2019.

Connects KNL1 loss to genome damage, aneuploidy surveillance, and brain progenitor elimination. It strengthens the bridge between kinetochore biology and progenitor survival.

Modern symbol

A novel KNL1 intronic splicing variant likely destabilizes the KMN complex, causing primary microcephaly

Fellows et al. American Journal of Medical Genetics Part A, 2023/2024.

Low citation count but high thesis value: it uses the modern KNL1 symbol and directly supports our decision to label rows with current HGNC terminology while running old data with CASC5.

4. Gabriel/Santpere developmental-genomics line: the modern cousin of the heatmap

Primary anchor

Early developmental origins of cortical disorders modeled in human neural stem cells

Mato-Blanco et al., with Gabriel Santpere as joint senior author. Nature Communications, 2025.

This is the most important modern bridge to the inherited plot. It studies expression dynamics of cortical and neuropsychiatric disorder genes in human neural stem cells across telencephalic fate transitions. It covers diseases from microcephaly/hydrocephaly to ASD, bipolar disorder, depression, anorexia, schizophrenia, Alzheimer disease, and Parkinson disease.

Earlier framework

Integrative functional genomic analysis of human brain development and neuropsychiatric risks

Li, Santpere, Kawasawa et al. Science, 2018.

A major PsychENCODE/BrainSpan-style paper linking human brain development, transcriptomics, regulation, and neuropsychiatric risk. It gives the larger intellectual background for crossing developmental expression with disease genetics.

2026 resource

NeMO Analytics: a compendium of transcriptomic data for the exploration of neocortical development

Sonthalia et al., including Gabriel Santpere. Nature Neuroscience, 2026. DOI: 10.1038/s41593-026-02204-4.

A very recent atlas/resource paper that consolidates transcriptomic data for neocortical development. For our project, it is a candidate source for a future, richer expression layer beyond the original CoGAPS matrices.

Evolution/regulation

The impact of human accelerated regions on neuronal development

Ruiz-Jiménez & Santpere. Trends in Genetics, 2025.

Short but conceptually relevant: it points toward human-specific regulatory evolution, developmental enhancers, and how brain developmental programs may be especially exposed to regulatory change.

5. Psychiatric, cognitive, and neurodevelopmental intersections

2025/2026 cross-disorder

Mapping the genetic landscape across 14 psychiatric disorders

Grotzinger, Werme, Peyrot et al. Nature, published Dec 2025; issue 2026. DOI: 10.1038/s41586-025-09820-3.

A major cross-disorder GWAS synthesis. It identifies five genomic factors, 238 pleiotropic loci, and broad enrichment for neurobiological processes. This is not an MCPH paper, but it is central for explaining the psychiatric side of the heatmap.

Functional variants

Massively parallel reporter assay investigates shared genetic variants of eight psychiatric disorders

Lee et al. Cell, 2025.

Strong because it moves from association to function: which shared psychiatric risk variants actually alter regulatory activity? This is the kind of evidence that a future atlas should prefer over simple gene overlap.

Fetal neurodevelopment

A genome-wide association study of shared risk across psychiatric disorders implicates gene regulation during fetal neurodevelopment

Schork, Won, Appadurai et al. Nature Neuroscience, 2019.

This paper gives a direct rationale for why a developmental microcephaly analysis can legitimately compare against psychiatric disorders: shared genetic risk points toward fetal neurodevelopmental regulatory programs.

Pleiotropy

Genomic Relationships, Novel Loci, and Pleiotropic Mechanisms across Eight Psychiatric Disorders

Lee et al. and PGC Cross-Disorder Group. Cell, 2019.

A heavily cited cross-disorder reference. It helps explain the logic of comparing ASD, ADHD, schizophrenia, bipolar disorder, depression, and related traits at the genetic level.

ASD rare variants

Rare coding variation provides insight into the genetic architecture and phenotypic context of autism

Fu, Satterstrom, Peng et al. Nature Genetics, 2022.

Useful for the ASD side of the atlas because it brings rare coding variation into the same broad interpretive space as de novo and inherited neurodevelopmental disorders.

Next research pass

What still needs to be deepened.

01

Gene-by-gene evidence review

The first matrix is now in this page. The next step is manual reading: verify each top PubMed paper, decide which one is the original disease paper, and distinguish disease-causing evidence from broad Open Targets associations.

02

Connected Papers graphs

Run separate graphs seeded by Mato-Blanco 2025, Phan & Holland 2021, Genin 2012, and Grotzinger 2025. Export screenshots and reconstruct a thesis-safe conceptual map.

03

Mario and group tracing

Mario appears in public traces mainly as a predoctoral researcher rather than as a clearly indexed MCPH author so far. Keep tracking UB/IBUB, Corominas/Rabionet/Casals/Cormand, and Gabriel's neurogenomics group.

04

Evidence grading

Turn the bibliography into a scoring table: causal MCPH evidence, mechanism clarity, relation to progenitors, relation to psychiatric/cognitive traits, and usefulness for explaining the plot.