Genotype Impacts Axial Length Growth in Pseudophakic Eyes of Marfan Syndrome.

Purpose: The purpose of this study was to investigate the relationship between axial length (AL) growth and FBN1 genotype in patients with Marfan syndrome (MFS) after lens surgery and customize the selection of intraocular lens (IOL) power. Methods: Patients with MFS who had lens surgery and primary IOL implantation received panel-based next-generation sequencing (NGS). The rate of axial length growth (RALG) was calculated using pre- and postoperative AL measurements and corrected log10-transformed age. A multivariable regression model of RALG was developed after analyzing the effect of FBN1 genotypes and confounding factors. Results: A total of 139 probands of MFS with a median age at lens surgery of 6.25 years (interquartile range [IQR] = 4.67, 12.50 years) were followed up for a median duration of 2.08 years (IQR = 1.16, 3.00 years). The AL growth curve between the age of 3 and 15 years old was logarithmic. Dominant-negative (DN) variants affecting the disulfide-bridge forming cysteines and the conserved residues for calcium-binding had significantly higher RALG than DN variants affecting other structures (P = 0.001) but comparable to that of haplo-insufficiency variants (P = 1.000). Pre-operative AL (b = 0.563, P = 0.011) and genotype constant (b = 2.603, P = 0.011) were significantly associated with RALG in the final model. A Python-based calculator, Marfan IOL Calculator version 2.0, was programmed using the RALG to predict postoperative AL and customize IOL selection based on the ocular biometric parameters and FBN1 genotype. Conclusions: FBN1 genotype impacted the growth of AL in patients with MFS after IOL implantation. Knowing the FBN1 genotype could help cataract surgeons to customize IOL selection.

Predicting axial length in patients with Marfan syndrome and ectopia lentis after modified capsular tension ring and intraocular lens implantation.

PURPOSE: To predict the growth of axial length (AL) in patients with Marfan syndrome (MFS) and ectopia lentis (EL). SETTING: Eye and ENT Hospital of Fudan University, Shanghai, China. DESIGN: Consecutive retrospective case series. METHODS: Eyes were evaluated that had modified capsular tension ring and intraocular lens (IOL) implantation. The rate of AL growth (RALG) was calculated using AL divided by log10-transformed age. A multivariate linear regression model of RALG was developed after validation. RESULTS: 128 patients with MFS and EL were enrolled with a median follow-up duration of about 3 years. RALG was independent of age between 3 years and 15 years old ( P = .799) and decreased to 0 thereafter ( P = .878). Preoperative AL was associated with RALG in patients under 15 years old ( P = .003). Beta values for the final model of RALG were as below: intercept (-9.794) and preoperative AL (0.664). The postoperative AL was predicted as: postAL = preAL + RALG × log 10 ([postAge + 0.6]/[preAge + 0.6]). The mean prediction error was -0.003 (95% CI, -0.386 to 0.3791) mm and the mean absolute percentage error was 1.93% (95% CI, 0.73% to 3.14%). A Python-based calculator was developed to use the predicted AL in selecting IOL power and setting undercorrection. CONCLUSIONS: The AL growth of patients with MFS followed a logarithmic pattern and ceased at about age 15. A prediction model of postoperative AL was established for individual MFS patients between 3 and 15 years old, which could potentially optimize the IOL power selection.

Supracapsular scleral sutured intraocular lens implantation in anterior segment dysgenesis patients with ectopia lentis.

OBJECTIVE: To describe a new strategy to manage ectopia lentis in ASD patients assessing the visual outcomes and safety of supracapsular scleral sutured intraocular lens implantation and analyzing the accuracy of different intraocular lens (IOL) power calculation formulae. METHODS: Eight patients with ASD (13 eyes) were underwent supracapsular scleral suture fixation of posterior chamber (PC) IOL without capsular extirpation. The preoperative and postoperative clinical features were compared. The prediction error values from four formulae (SRK/T, Holladay 1, Hoffer Q, Haigis), with or without Wang-Koch (WK) adjustment, were calculated for the cases. RESULTS: Zonulodialysis and premature cataracts could be the main reason for the decreased vision in patients with ASD. There was a significant improvement in best corrected visual acuity on 3-month follow-up after applying supracapsular scleral suture fixation of PC IOL. The prediction errors of the different formulae showed a slight tendency towards postoperative myopia. The Haigis formula with WK adjustment showed the best performance. CONCLUSIONS: Supracapsular scleral suture fixation of IOLs for retaining the capsule-zonule barrier is a good option for ASD patients. The Haigis formula is recommended for ASD patients treated with supracapsular scleral suture fixation of IOLs. The predicted IOL power should be reduced based on the effect of the new anatomic position of the IOL to achieve a satisfactory visual outcome.

Biallelic ADAMTSL4 variants in a Chinese cohort of congenital ectopia lentis: Implications for genotype-phenotype relationships.

ADAMTSL4 variants are one of the common causes of congenital ectopia lentis (EL), reported ocular comorbidities of which include iris anomalies, cataract, and glaucoma. However, a genotype-phenotype correlation has not been established. Potentially pathogenic ADAMTSL4 variants were screened from a Chinese cohort of congenital EL using panel-based next-generation sequencing followed by multiple bioinformatics analyses. The genotype-phenotype correlation was assessed via a systematic review of ADAMTSL4 variants within our data and those from the literature. A total of 12 variants of ADAMTSL4, including seven frameshift variants, one nonsense variant, two splicing variants, and two missense variants, were found in nine probands. Combing genetic and clinical information from 72 probands in the literature revealed 37 ADAMTSL4 variants known to cause EL, and the ethnic difference was prominent. The lens was inclined to dislocate inferior temporally (22, 27.16%), while the pupil was always located oppositely (9, 81.82%). Several anterior segments anomalies were identified, including ectopia pupillae (15, 18.52%), persistent pupillary membrane (9, 11.10%), poor pupil dilation (4, 30.8%), cataract (13, 24.10%), and glaucoma (8, 13.33%). Genotype-phenotype analysis revealed that truncation variants had higher risks of combined iris anomalies, including either ectopia pupillae or a persistent pupillary membrane (p = 0.007). The data from this study not only extend our knowledge of the ADAMTSL4 variant spectrum but also suggest that deleterious variants of ADAMTSL4 might be associated with severe ocular phenotypes.

Comparison of Accuracy in Keratometries Measured by Different Camera Devices for Predicting the Intraocular Lens Power in Lens-Dislocated Patients.

INTRODUCTION: This is a cross-sectional cohort study focused on assessing the influence of ocular biometric parameters of different camera devices for accurately predicting the intraocular lens (IOL) power in the congenital ectopia lentis (EL) patients. METHODS: This study includes a total of 91 eyes of 60 patients with congenital EL from June 2018 to April 2021. All patients underwent lens subluxation surgery with Cionni modified capsular tension rings (MCTR) implantation. Ocular parameters measured by partial coherence interferometry (IOLMaster 700, Carl Zeiss Meditec AG, Jena, Germany) and rotating Scheimpflug camera (Pentacam HR system, Oculus Optikgeräte GmbH, Wetzlar, Germany) were acquired from the database. The authenticity of the different keratometries (K) were analyzed by comparing the prediction error in spherical equivalent under controlled formula SRK/T, Haigis, and after Wang-Koch (WK) adjustment. RESULTS: We observed significant greater K values were obtained in IOLMaster than Pentacam, resulting in more significant hyperopia error while calculating SRK/T. The IOL power calculated with the total corneal refractive power (TCRP) from Pentacam revealed the highest prediction accuracy, indicating that TCRP is the closest to the actual refractive power of the cornea. However, in an exceptional case for long eye patients, total keratometry from IOLMaster was better recommended when using formula Haigis with WK adjustment. CONCLUSIONS: For most instances, TCRP is the best-recommended source of K value while calculating IOL power for EL patients. However, the total keratometry from IOLMaster preferably fits for long eye patients, who require WK adjustment for Haigis formula.