Evagene adds polygenic inheritance, nine cancer family-history models, and CanRisk export

1. Polygenic, oligogenic, and multifactorial inheritance

Most common diseases cluster in families but do not follow Mendelian patterns. Evagene now ships a full liability-threshold recurrence-risk engine grounded in the classical genetic epidemiology of Carter, Falconer, and Reich/James/Morton ^[1][2][3]. For each counselee, the engine:

• Classifies affected relatives by degree — MZ twin / 1st / 2nd / 3rd / 4th degree.
• Uses empirical recurrence-risk tables (Smith, Carter, Harper) when available ^[4].
• Falls back to a Falconer liability-threshold calculation from heritability (h²) and prevalence (K) when an empirical table is absent.
• Applies four classical counselling modifiers: severity of proband, Carter-effect sex bias, multiple affected close relatives, and parental consanguinity as (1 + 2F·h²).

Twenty-three complex conditions are catalogued with heritability and empirical recurrence-risk data: cleft lip ± palate, cleft palate only, Hirschsprung's disease, type 1 and type 2 diabetes, late-onset Alzheimer's, idiopathic Parkinson's, ankylosing spondylitis, schizophrenia, bipolar disorder, major depression, epilepsy, pyloric stenosis (the classic Carter-effect disorder), neural tube defects, congenital heart disease, talipes, developmental dysplasia of the hip, asthma, atopic dermatitis, coeliac disease, essential hypertension, obesity, and allergic rhinitis. Each carries a dedicated in-app help page covering inheritance, recurrence risks by relationship, susceptibility loci, clinical features, and counselling points.

Model labels MULTIFACTORIAL, POLYGENIC, and OLIGOGENIC share the same engine and differ only in which aetiological label best fits the disease. Users browsing the complex-disease catalogue can filter by inheritance class.

2. Cancer family-history risk models — complementing BRCAPRO / MMRpro / PancPRO

All models below are implemented in Python and run without an R sidecar. Each answers a specific counselling question; pick the one that matches the need.

Claus model

CASH-derived lifetime breast-cancer risk as a function of the number, degree of relationship, and age at diagnosis of affected relatives, with an ovarian-in-first-degree multiplier ^[5]. Best for women who do not meet NICE high-risk criteria but want a numerical lifetime estimate.

Couch model

A logistic-regression pre-test probability of a BRCA1 mutation using three features: average age at breast-cancer diagnosis in the family, ovarian cancer in the family, and Ashkenazi Jewish ancestry ^[6]. Output includes a 10% testing-threshold flag.

Frank / Myriad model

Empirical BRCA1 and BRCA2 mutation frequencies in women sent for testing, by canonical family scenario (e.g. proband with breast cancer <40 and family ovarian cancer) ^[7]. Useful for the quickest clinic-friendly answer to "how likely is a positive BRCA test?"

Manchester Scoring System

Point-based scoring assigning points per cancer type and age at diagnosis, separately for BRCA1 and BRCA2, across the proband and first- and second-degree relatives ^[8]. BRCA1 score ≥ 16 ≈ 10% carrier probability; BRCA2 score ≥ 16 ≈ 10%; combined ≥ 20 ≈ 20%. Widely used by NHS genetics services in the UK.

NICE CG164 / NG101 familial breast cancer categorisation

Implements the family-history categorisation from NICE CG164 (2013) and its NG101 update (2019 / 2023) ^[9][10]. Pedigrees are checked against classical high- and moderate-risk triggers and classified as near-population (<1 in 6 lifetime), moderate (1 in 6 to 1 in 3), or high (>1 in 3), with a refer-to-genetics flag and the specific triggers matched.

Amsterdam II criteria

Classical HNPCC / Lynch-syndrome family-history criteria (Vasen et al. 1999) ^[11]. Evagene evaluates the pedigree-derivable conditions directly; the exclusion-of-FAP and histology checks are surfaced as clinical-verification notes.

Revised Bethesda Guidelines

Triggers for MSI / IHC testing of a colorectal tumour (Umar et al. 2004) ^[12]. Complements Amsterdam II — families that do not meet classical Amsterdam II may still meet Bethesda.

Gail model (NCI BCRAT)

Mitchell Gail's breast-cancer risk assessment tool, hosted by the US National Cancer Institute (Gail 1989, with updates through 2017) ^[13]. Combines age at menarche, age at first live birth (or nulliparity), number of first-degree relatives with breast cancer, number of prior benign breast biopsies, atypical hyperplasia, and race/ethnicity baselines. Produces an individualised 5-year and lifetime breast-cancer risk. Not valid for women with prior invasive BC, DCIS, LCIS, or a known high-penetrance mutation — use BRCAPRO or the CanRisk export instead.

Tyrer-Cuzick — IBIS-style approximation

An implementation of the Tyrer-Cuzick algorithm (Tyrer, Duffy & Cuzick 2004) ^[14], covering full family history, menarche, menopause, parity, age at first live birth, hormone-therapy years, BMI, atypical hyperplasia, LCIS, benign biopsies, mammographic density (BI-RADS 1–4), and Ashkenazi ancestry.

3. CanRisk / BOADICEA pedigree export

The NICE-recommended model for moderate- and high-risk women is BOADICEA, hosted at canrisk.org. It integrates multi-gene panel testing (BRCA1, BRCA2, PALB2, CHEK2, ATM, BARD1, RAD51C, RAD51D, BRIP1), polygenic-risk scores, and mammographic density to produce breast- and ovarian-cancer risk curves ^[15][16].

Evagene now ships a one-click download of a BOADICEA v4 / CanRisk v2 pedigree file (tab-separated, ##CanRisk 2.0 header) populated with the pedigree structure, ages at diagnosis, BRCA1 / BRCA2 / PALB2 / ATM / CHEK2 test statuses, Ashkenazi flag, and reproductive factors. The clinician uploads the file at canrisk.org and runs the full workup there.

4. Reproductive / breast-health fields on Individual

To support Gail, Tyrer-Cuzick, and the CanRisk export, the Individual record gains structured reproductive and breast-health fields:

• Age at menarche, age at menopause, age at first live birth, parity.
• Cumulative hormone-therapy years.
• Number of prior benign breast biopsies; atypical hyperplasia flag; LCIS flag.
• Mammographic density (BI-RADS 1–4).
• Height and weight for BMI.

These fields are optional; models that require them display a clear warning when a required field is missing and cannot be defaulted.

5. What Evagene does not claim

Evagene's risk models are decision-support tools that augment, not replace, the clinical geneticist. The expansion ships with these explicit boundaries:

• No regulatory approval. Evagene is not an FDA-cleared medical device and is not equivalent to validated clinical-trial-grade risk tools such as the official IBIS or CanRisk binaries.
• Tyrer-Cuzick is an approximation of the published algorithm, not the official IBIS v8 binary. Every result is labelled in the UI.
• BOADICEA is not bundled; Evagene provides a pedigree export that the clinician uploads at canrisk.org.
• All models assume accurate, complete pedigree data. Missing individuals, unknown ages, and unrecorded diagnoses reduce reliability.

Related pages

• Hereditary cancer risk assessment — clinical logic for BRCAPRO / MMRpro / PancPRO plus the family-history models.
• Decision matrix: which risk model for which counselling question?
• Complex-disease pedigree software — the 23 catalogued multifactorial conditions with recurrence risks and links to in-app help.
• Mendelian inheritance calculator — AD, AR, and XLR models for single-gene work.

Citations

1. Carter CO. The inheritance of pyloric stenosis. Br Med Bull. 1961;17:251–254.
2. Falconer DS. The inheritance of liability to certain diseases, estimated from the incidence among relatives. Ann Hum Genet. 1965;29:51–76.
3. Reich T, James JW, Morton CA. The use of multiple thresholds in determining the mode of transmission of semi-continuous traits. Ann Hum Genet. 1972;36:163–184.
4. Smith C. Recurrence risks for multifactorial inheritance. Am J Hum Genet. 1971;23:578–588.
5. Claus EB, Risch N, Thompson WD. Autosomal dominant inheritance of early-onset breast cancer. Implications for risk prediction. Cancer. 1994;73:643–651.
6. Couch FJ, DeShano ML, Blackwood MA, et al. BRCA1 mutations in women attending clinics that evaluate the risk of breast cancer. N Engl J Med. 1997;336:1409–1415.
7. Frank TS, Deffenbaugh AM, Reid JE, et al. Clinical characteristics of individuals with germline mutations in BRCA1 and BRCA2: analysis of 10,000 individuals. J Clin Oncol. 2002;20:1480–1490.
8. Evans DG, Eccles DM, Rahman N, et al. A new scoring system for the chances of identifying a BRCA1/2 mutation outperforms existing models including BRCAPRO. J Med Genet. 2004;41:474–480.
9. NICE. Familial breast cancer: classification, care and managing breast cancer and related risks in people with a family history of breast cancer. NICE Clinical Guideline CG164. 2013.
10. NICE. Early and locally advanced breast cancer: diagnosis and management. NICE Guideline NG101. 2018; updated 2023.
11. Vasen HF, Watson P, Mecklin JP, Lynch HT. New clinical criteria for hereditary nonpolyposis colorectal cancer (HNPCC, Lynch syndrome) proposed by the International Collaborative Group on HNPCC. Gastroenterology. 1999;116:1453–1456.
12. Umar A, Boland CR, Terdiman JP, et al. Revised Bethesda Guidelines for hereditary nonpolyposis colorectal cancer (Lynch syndrome) and microsatellite instability. J Natl Cancer Inst. 2004;96:261–268.
13. Gail MH, Brinton LA, Byar DP, et al. Projecting individualized probabilities of developing breast cancer for white females who are being examined annually. J Natl Cancer Inst. 1989;81:1879–1886.
14. Tyrer J, Duffy SW, Cuzick J. A breast cancer prediction model incorporating familial and personal risk factors. Stat Med. 2004;23:1111–1130.
15. Antoniou AC, Pharoah PPD, Smith P, Easton DF. The BOADICEA model of genetic susceptibility to breast and ovarian cancer. Br J Cancer. 2004;91:1580–1590.
16. Lee A, Mavaddat N, Wilcox AN, et al. BOADICEA: a comprehensive breast cancer risk prediction model incorporating genetic and nongenetic risk factors. Genet Med. 2019;21:1708–1718.